Degree: Bachelor of Computer Science 180hp Supervisor(s): Céline Fernandez,
Major: Information Systems Annabella Loconsole
Tech n ology a n d s ociet y Com p u t er S cien ce
In vest iga t ion of Pa t h wa y An a lysis
Tools for m a ppin g om ics da t a t o
pa t h wa ys
-Focu s on l i p i d om i cs a n d gen om i cs d a t a
Un der sök n in g a v a n a lysver k t yg för a t t k a r t lä gga om ik da t a
t ill r ela t ion svä ga r
– F ok u s p å d a t a a v t y p en l i p i d om i k och g en om i k
A n ed u cation isn 't h ow m u ch you h ave com m itted to m em ory,
or even h ow m u ch you k n ow . It's bein g able to d ifferen tiate
betw een w h at you k n ow an d w h at you d on 't.
/An a t ole F r a n ce
Ac k n o w le d g e m e n t s
I wou ld lik e sa y t h a n k you t o ever yon e wh o h elped m e wit h m y t h esis. To m y su per visor s I t h a n k you for you r pa t ien ce, gu ida n ce a n d a ll t h e good feedba cks.
Abst r a ct
Th is t h esis exa m in es P ATs fr om a m u lt idisciplin a r y view. Th er e a r e a lot of P AT's exist in g t oda y a n a lyzin g specific t ype of om ics da t a , t h er efor e we in vest iga t e t h em a n d wh a t t h ey ca n do. By defin in g som e specific r equ ir em en t s su ch a s h ow m a n y om ics da t a t ypes it ca n h a n dle, t h e a ccu r a cy of t h e P AT ca n be obt a in ed t o get t h e m ost su it a ble P AT wh en it com es t o m a ppin g om ics da t a t o pa t h wa ys . Resu lt s sh ow t h a t n o P ATs fou n d t oda y fu lfills t h e specific set of r equ ir em en t s or t h e m a in goa l t h ou gh soft wa r e t est in g. Th e In gen u it y P AT is t h e closest t o fu lfill t h e r equ ir em en t s . Requ est ed by t h e en d u ser , t wo P ATs a r e t est ed in com bin a t ion t o see if t h ese ca n fu lfill t h e r equ ir em en t s of t h e en d u ser . U n ipr ot ba t ch con ver t er wa s t est ed wit h F E vE R a n d r esu lt s did n ot t u r n ou t su ccessfu lly sin ce t h e com bin a t ion of t h e t wo P ATs is n o bet t er t h a n t h e In gen u it y P AT. F ocu s t h en t u r n ed t o a n a lt er n a t ive com bin a t ion , a h om epa ge ca lled N CBI t h a t h a ve sea r ch en gin es con n ect ed t o sever a l fr ee P ATs a va ila ble t h u s fu lfillin g t h e r equ ir em en t s. Th r ou gh t h e sea r ch en gin e “om ics” da t a ca n be com bin ed a n d m or e t h a n on e in pu t ca n be t a k en a t a t im e. Sin ce t ech n ology is r a pidly m ovin g for wa r d , t h e n eed for n ew t ools for da t a in t er pr et a t ion a lso gr ows. It m ea n s t h a t in a n ea r fu t u r e we m a y be a ble t o fin d a P AT t h a t fu lfills t h e r equ ir em en t s of t h e en d u ser s.
Ke y w o rd s : Bioch em ist r y, Ca r diova scu la r disea se, Da t a ba se, Gen om ics, Lipids,
Lipidom ics, Met a bolom ics, P AT, Tech n ology
Sa m m a n fa t t n in g
Det t a exa m en sa r bet e gr a n sk a r a n a lysver kt yg u r et t t vä r vet en sk a pligt per spek t iv. Det fin n s en h el del olik a a n a lysver kt yg ida g som a n a lyser a r specifik a t yper a v om ik da t a och dä r för u n der sök er vi h u r m å n ga det fin n s sa m t va d de k a n gör a . Gen om a t t defin ier a et t a n t a l specifik a k r a v så som h u r m å n ga t yper a v om ik da t a den k a n h a n t er a , n oggr a n n h et a v ver k t yget s a n a lys så k a n m a n se vilk a som ä r m est lä m pliga a n a lysver kt ygen n ä r det gä ller k a r t lä ggn in g a v om ik da t a . Resu lt a t en visa r a t t det ida g in t e fin n s a n a lysver k t yg som u ppfyller de specifik t a n givn a k r a ven eller h u vu dsyft et gen om t est n in g a v pr ogr a m va r a n . In gen u it y a n a lysver kt yget ä r det n ä r m a st e vi k a n k om m a för de k r a v som vi sök er . P å begä r a n a v slu t a n vä n da r en t est a des t vå a n a lysver kt yg för a t t se om en k om bin a t ion a v dessa k a n u ppfylla slu t a n vä n da r en s k r a v. An a lysver k t yget U n ipr ot ba t ch con ver t er t est a s m ed F E vE R m en r esu lt a t ä r in t e fr a m gå n gsr ikt , då k om bin a t ion en a v dessa ver kt yg in t e ä r bä t t r e ä n In gen u it y a n a lysver kt yget . F ok u s vä n ds m ot en a lt er n a t iv k om bin a t ion som ä r en h em sida och h et er N CBI. H em sida n h a r en sök m ot or k oppla d t ill fler a olik a a n a lysver kt yg som ä r gr a t is a t t a n vä n da . Gen om sök m ot or n k a n ”om ik ” da t a k om bin er a s och m er ä n et t in m a t a t vä r de k a n h a n t er a s i t a get . E ft er som t ek n ik en sn a bbt gå r fr a m å t in n ebä r det dä r em ot a t t n ya a n a lysver k t yg beh övs för da t a h a n t er in g och in om en sn a r fr a m t id så h a r vi k a n sk e et t a n a lysver kt yg som u ppfyller k r a ven a v slu t a n vä n da r n a .
N y c k e lo rd : Biok em i, Ka r diova sk u lä r sju k dom , Da t a ba s, Gen om ik, L ipider , Lipidom ik,
Co n t e n t s
Abst r a ct ... 3
Sa m m a n fa t t n in g ... 3
1. In t r odu ct ion ... 5
1.1. P u r pose ... 5
1.2. P r oblem defin it ion s a n d Aim s ... 6
1.3. P r oblem discu ssion ... 6
1.4. Rela t ed wor k wit h P AT ... 8
2. Met h ods ... 8
2.1. Model in u se ... 8
2.1.1. R equ irem en t collection , d ocu m en tation an d valid ation ... 8
2.1.2. R equ irem en t processin g an d test case creation ... 9
2.1.3. Objective ... 12
2.1.4. U n d erlyin g objectives ... 12
2.2. Alt er n a t ive r esea r ch m et h ods ... 13
3. Biom edica l backgr ou nd ... 13
3.1. Gen et ics ... 13
3.1.1. Gen e ... 14
3.1.2. S N P ... 15
3.2. Bioch em ist r y of Lipids ... 16
3.2.1. L ipid d efin ition ... 17
3.2.2. Classes of L ipid s ... 17
3.2.3. E n zym es in volved in th e syn th esis of lipid s ... 18
3.2.4. L ipoprotein s ... 21
3.3. Gen om ics ... 21
3.4. Met a bolom ics ... 22
3.5. Lipidom ics ... 22
3.6. Ca r diova scu la r disea ses ... 22
4. Com pu t er Scien ce ba ckgr ou n d ... 23
4.1. Da t a ba ses, Da t a m in in g a n d Kn owledge discover y ... 23
4.2. P AT ... 23
5. Requ ir em ent s a n d Test elicit at ion ... 24
5.1. Requ ir em en t s ... 24 5.2. Test in g ... 25 5.3. Test ca ses ... 26 6. Resu lt ... 26 6.1. F in din g t h e P ATs ... 26 6.2. Sor t in g t h e P ATs ... 27 6.3. Test in g t h e P ATs ... 27 6.4. E va lu a t in g t h e P ATs ... 28
6.5. F in a l eva lu a t ion of t h e P ATs ... 28
6.6. Th e best P AT fr om t h e r a n k ed list ... 29
6.7. Com bin in g P ATs ... 31
6.8. F u n ct ion a lit ies ... 34
6.9. Qu a lit y ... 35
7. Discu ssion ... 36
7.1. Is it possible t o fin d a P AT t h a t pr ocesses m et a bolom ics a n d lipidom ics r a w da t a a s in pu t a n d com bin e t h em wit h gen et ic in for m a t ion ? ... 36
7.2. Wh a t a r e t h e fu n ct ion a lit ies offer ed by t h e a va ila ble a n a lysis t ools? ... 36
7.4. Wh y n ot In gen u it y a n d wh y U n ipr ot wit h F E vE R? ... 38
8. F u t u r e Va lu e ... 38
9. Refer en ces ... 38
Appen dix 1 – Test Ca ses ... 42
Appen dix 2 – Lipid, MI SN P a n d Met a bo SN P da t a sh eet ... 46
Appen dix 3 – Requ ir em en t s Ma t r ixes ... 50
Appen dix 4 – Respon s Tim es ... 53
1. In t r odu ct ion
Va st a m ou n t s of r esea r ch is don e in lipidom ics a n d gen om ics, m a kin g com pu t er s, In t er n et a n d va r iou s a n a lysis t ool's ver y com m on t oda y bot h in sim ple a n d a dva n ced for m s. As a n exa m ple a sim ple ca lcu la t ion ca n be per for m ed on on e com pu t er a n d t r a n sfer r ed or copied t o a n ot h er if n eeded. Mor e a dva n ced per for m a n ces som et im es r equ ir e a soft wa r e t ool t h a t ca n per for m a cer t a in t a sk on a given set of da t a in or der t o give a cer t a in r esu lt . Th e r esu lt is in t u r n u su a lly n ot logica lly or der ed a n d a visu a l pr esen t a t ion is n eeded. Th is is wh er e a pa t h wa y a n a lysis t ool (P AT) is n eeded. A pa t h wa y a n a lysis t ool (P AT) is a n a dva n ced t ool t h a t pr ocess es given da t a , com pa r es t h e given da t a wit h st or ed da t a in a da t a ba se a n d pr esen t s t h e r esu lt s obt a in ed visu a lly. A com pa n y t en ds t o h ir e a pr ogr a m m er t o develop a pa t h wa y a n a lysis t ool (P AT) in or der t o in t egr a t e it wit h in t h e or ga n iza t ion [34]. On e of t h e m a in gr ou p s of scien t ific u ser s is t h e gr ou p of r esea r ch er s in fields of bioin for m a t ics, gen et ics, gen om ics a n d m et a b olom ics. Resea r ch er s a r e depen den t of t h ese pa t h wa y a n a lysis t ools in t h eir scien t ific wor k. In som e scien t ific fields su ch a s gen om ics a n d m et a bolom ics, t h er e a r e t oo m a n y a n a lysis t ools (P AT), doin g a ll kin ds of differ en t t a sks. Too m a n y pa t h wa y a n a lysis t ools in a specific field ca n con fu se r esea r ch er s wh o do n ot h a ve en ou gh kn owledge in t ech n ology [5]. Th is m a kes it difficu lt t o decide wh a t pa t h wa y a n a lysis t ools a r e su it ed for cer t a in da t a a n d wit h in wh a t scien t ific field. Sin ce t ech n ology is a lso m ovin g for wa r d ext r em ely fa st , people wit h m u lt idisciplin a r y kn owledge a r e n eeded m or e a n d m or e [20]. F or r esea r ch er s wh o wor k wit h in t h e biom edica l field of m et a bolom ics a n d gen om ics t h er e a r e specific a n a lysis t ools. Th e pu r poses of t h ese pa t h wa y a n a lysis t ools (P AT) a r e t o h elp t h e u ser s in t h eir wor k, wh er e t h ey ca n visu a lize da t a t h a t m a y lea d t o n ew scien t ific discover y. Tech n ology a n d in for m a t ion sh a r in g h a s t a ken a big st ep for wa r d a n d h a s h elped su bst a n t ia lly in differ en t a r ea s a r ou n d t h e wor ld su ch a s in h ea lt h ca r e a n d m edicin e.
1.1.P u rp o s e
F in din g r elia ble pa t h wa y a n a lysis t ools (will be r efer r ed t o a s P AT fr om n ow on ) t h a t ca n do a ll t h e n ecessa r y da t a com pu t a t ion s a n d ca n visu a lly pr esen t t h e r esu lt s is r equ est ed by Célin e F er n a n dez fr om Clin ica l Resea r ch Cen t er (CRC) in Ma lm ö (will be r efer r ed t o a s t h e en d u ser ). CRC wor k s in discover in g n ew m edicin e, dia gn ost ic t ools a n d im pr oved t r ea t m en t s in or der t o im pr ove h ea lt h wor ldwide.
1.2.P ro b le m d e fi n i t i o n s a n d Ai m s
Sin ce t h er e a r e m a n y P AT a va ila ble wit h lot s of in for m a t ion , t h e followin g r esea r ch qu est ion s a r e defin ed in t h is t h esis:
Is it possible t o fin d a P AT t h a t pr ocesses m et a bolom ics a n d lipidom ics r a w da t a a s in pu t a n d com bin es t h em wit h gen et ic in for m a t ion ?
Wh a t a r e t h e fu n ct ion a lit ies offer ed by t h e a va ila ble a n a lysis t ools?
Wh a t a r e t h e qu a lit ies of t h ese t ool's a n d h ow t o eva lu a t e t h em ? Th e object ives a r e defin ed in or der t o h elp a n swer t h e t h r ee r esea r ch qu est ion s. Th e m a in a im of t h is t h esis is t h e followin g:
To fin d a P AT t h a t ca n pr ocess a com bin a t ion of da t a in pu t s wit h t h e t ype of “om ics” da t a , i.e. lipidom ics/m et a bolom ics, genom ics da t a .
In or der t o r ea ch t h e m a in pu r pose, sever a l u n der lyin g object ives a r e n eeded. Th ese a r e t h e followin g:
1) F in d P ATs t h a t a r e a ble t o m a p pa t h wa ys of t h e followin g t ype of da t a : a ) Over a ll m et a bolom ics da t a
b) Lipidom ics da t a c) Gen om ics da t a
2) E va lu a t e t h e select ed P AT a n d t h eir fu n ct ion s. Test t h e cu r r en t a ccu r a cy of t h e exist in g P AT in or der t o a n swer if t h e ou t pu t fr om t h ese t ools sh ows t h e “cor r ect ” r esu lt s.
3) E va lu a t e t h e select ed P AT a ccor din g t o specific r equ ir em en t s given by t h e en d u ser ; see sect ion 1.3 for t h e specific r equ ir em en t s.
Aft er t h e eva lu a t ion of t h e P AT a ccor din g t o r equ ir em en t s, t wo opt ion s a r e possible:
Opt ion 1: On e or m or e P AT pa sses st eps 2 a n d 3 a n d is deliver ed t o t h e en d u ser .
Opt ion 2: If n o P AT fu lfillin g t h e r equ ir em en t s is fou n d. Alt er n a t ive solu t ion s will be t o see if it is possible t o a da pt a n y of t h e eva lu a t ed a n a lysis t ools, com bin e m or e t h a n on e or m a ke a n in h ou se developm en t of a P AT m eet in g t h e r equ ir em en t s of t h e en d u ser .
1.3.P ro b le m d i s c u s s i o n
In or der t o solve t h e pr oblem we m u st con sider wh a t P ATs a r e, h ow com plex t h ey a r e a n d wh a t t h ey ca n do. T h e fu n ct ion a lit ies of t h e P AT n eed t o be t est ed [28] t o see if t h ey fu lfill t h e specific r equ ir em en t s (S ee T able 1).
Ta b le 1. 8 specific r equ ir em en t s list ed t h a t n eeds t o be fu lfilled by a P AT. R e q u i re m e n t
ID
R e q u i re m e n t d e s c ri p t i o n
1 U ser is a ble t o see a n d select on t h e P AT wh a t t ype of da t a it m u st pr ocess (if t h e in pu t field is for m et a bolom ic, lipidom ic or gen om ic)
2 U ser m u st be a ble t o con t r ol if obt a in ed r esu lt is va lid fr om t h e P AT a ccor din g t o lit er a t u r e, In t er n et or la bor a t or y r esu lt s
3 Th e u ser m u st r eceive r esu lt s by t h e P AT wit h in a cer t a in t im e
4 Th e u ser ca n n a viga t e bet ween st a r t of sea r ch (in pu t da t a ) t o t h e en d of sea r ch (r esu lt s obt a in ed).
5 Th e u ser ca n get a visu a l pr esen t a t ion of m et a bolom ics, lipidom ics a n d gen om ics da t a fr om t h e P AT
6 Th e u ser ca n zoom in a n d ou t expa n din g t h e view t o n eigh bor in g possible r esu lt s t o see con n ect ed pa t h wa ys on t h e r eceived r esu lt s fr om t h e P AT.
7 Th e u ser ca n in pu t a specific t ype of da t a in t o t h e P AT (m et a bolom ic, lipidom ic or gen om ic)
8 Th e u ser ca n in pu t com bin ed om ics da t a a n d t h en m a p t h em t o pa t h wa ys
Acqu ir in g kn owledge fr om lit er a t u r e gives u s in for m a t ion a bou t t h e com plexit y of a P AT [27]. Th e fu n ct ion a lit ies fr om a P AT ca n be obt a in ed wit h h elp of soft wa r e t est in g of da t a in pu t s [9] a n d t h is wa y we ca n ch eck if t h e P AT sa t isfy t h e r equ ir em en t s of t h e pot en t ia l u ser s. Th e defin it ion of qu a lit y is of a bigger sca le a n d h a r der t o defin e sin ce qu a lit y h a s differ en t m ea n in gs t o differ en t people [36]. Th e qu a lit ies of t h e P AT a r e a ccept a ble if t h ey a r e fu lfillin g a ll t h e r equ ir em en t s [36] a ccor din g t o a set of r equ ir em en t specifica t ion s. We will be u sin g t h e r equ ir em en t specifica t ion s a ccor din g t o t a ble 1. H om epa ges a ssocia t ed wit h P AT a lso n eed t o be qu a lit y ch ecked a n d five select ed a spect s a r e u sed: A ccu racy an d Correctn ess (h ow t r u st wor t h y is t h e in for m a t ion pr ovided on t h e h om epa ges), Com pleten ess (a r e t h e h om epa ges com plet e or u n der con st r u ct ion ), R elevan ce (h ow r eleva n t is con t en t or in for m a t ion on a h om epa ge t o t h e P AT), T im e an d Pu n ctu ality (h ow fa st ca n a h om epa ge be fou n d wh en sea r ch in g), T raceability (is t h e in for m a t ion pr ovided on t h e h om epa ges t r a cea ble t o t h eir or igin a l sou r ce).
1.4.R e la t e d w o rk w it h P AT
Most P AT t oda y is m a de specifica lly wit h focu s on m et a bolom ics a n d gen om ics. Th is is du e t o t h e r esea r ch wor k in m et a bolic en gin eer in g, cellu la r m et a bolism a n d in t oxic gen om ics [16, 25]. Com pa n ies spen d va st a m ou n t s of m on ey developin g a P AT wh ile t r yin g t o com pet e wit h ea ch ot h er [8, 15]. Th e com pet it ion for t h e com pa n ies in volves bu ildin g, a da pt in g a n d eva lu a t in g ea ch ot h er 's P AT, t ellin g wh y t h eir P AT is bet t er t h a n t h e ot h er [8, 15, 33]. Sin ce t h e P AT is specifica lly developed for a biom edica l field [41], t h er e exist s n o fu ll-sca le a n a lysis on t h e en t ir e P AT yet . Ou r st u dy is a fir st a t t em pt a t su ch a n a n a lysis of a com plet e set of a ll P AT.
2. Met h ods
Th is sect ion descr ibes t h e scien t ific m et h ods u sed t o eva lu a t e t h e differ en t P AT. St a r t in g wit h t h e select ed m et h od in u se, h ow t h e in for m a t ion is ga t h er ed a n d det a ils on t h e object ives a n d u n der lyin g object ives.
2.1.Mo d e l i n u s e
Th e m a in pu r pose (t o fin d a P AT t h a t ca n pr ocess a com bin a t ion of da t a input s wit h t he t ype of “om ics” da t a , i.e. lipidom ics/m et abolomics, genom ics da t a ) of t h e pr oject wa s divided in t o fou r u n der lyin g object ive, ea ch wit h it s specific object ive. Met h ods t h a t will be per for m ed a r e ba sed on a n em pir ica l m odel wit h a st u dy on P AT in or der t o t est a n d a n a lyze ea ch of t h e P AT a n d t h eir h om epa ges. Test ca ses a r e design ed ba sed on t h e r equ ir em en t s fr om t h e en d u ser a t t h e fir st in t er view. Th e r equ ir em en t s a r e r ech ecked a few weeks la t er wit h t h e en d u ser in a secon d in t er view. On ce a ckn owledged, t h e soft wa r e t est in g begin s wit h r equ ir em en t s a n d t est ca ses, in or der t o see if in goin g da t a m a t ch es t h e ou t com in g da t a of t h e P AT. Da t a is ba sed on a gen e n a m e (e.g. N P P A), r efer en ce SN P a ccession ID (r s n u m ber su ch a s r s5068) or a lipid cla ss n a m e (su ch a s lipopr ot ein s). Ver ifica t ion (fr om t h e P AT) of t h e ou t com in g da t a t o see if it s r eleva n t is per for m ed by com pa r in g t h e r eceived r esu lt s wit h in for m a t ion fou n d in lit er a t u r e. A r a n ked list is m a de r a n kin g t h e best P AT fir st , ba sed on h ow m a n y r equ ir em en t s a r e m et . If n o P AT m eet s a ll t h e r equ ir em en t s, t h e en d u ser h a ve a r equ est t o a da pt or com bin e 2 specifica lly select ed t ools, wh ich en d u ser is a lr ea dy fa m ilia r ized wit h , wh ile t h e r a n ked list get s disca r ded .
2.1.1. R equ irem en t collection , d ocu m en tation an d valid ation
F ive m eet in gs a r e booked a t t h e Clin ica l Resea r ch Cen t er (CRC) in or der t o m a ke in t er views. All pa r t icipa n t s (r esea r ch er s in clu din g t h e en d u ser ) a r e goin g t o discu ss a bou t t h e pr oblem t h a t n eeds t o be solved. Discu ssion will focu s on P AT in gen er a l a n d specific fu n ct ion s a r e goin g t o be desir ed by t h e r esea r ch er s t h a t h a ve t o be on a P AT. Requ ir em en t s a r e m a de con n ect ed t o t h ese fu n ct ion s on a P AT a n d a n ew m eet in g is booked . Du r in g ea ch m eet in g ever yt h in g is wr it t en down a n d docu m en t ed. Aft er ea ch m eet in g,
r equ ir em en t s a r e collect ed t o be sor t ed a n d pr ocessed in or der t o m a ke t est ca ses. La t er a ch ecku p t a kes p la ce a t sa m e pla ce, t o see if ever yt h in g is on t h e r igh t t r a ck .
2.1.2. R equ irem en t processin g an d test case creation
Th e r equ ir em en t s a r e pr ocessed a n d for m u la t ed. Th ey a r e a lso sh or t en ed down fr om 15 t o eigh t r equ ir em en t s wit h t h e m ost im por t a n t t h in gs t h a t a P AT m u st do. E a ch of t h e r equ ir em en t s is given a n iden t ifica t ion n u m ber . Test ca se t em pla t es a r e sou gh t a n d on e t em pla t e is select ed, down loa ded a n d t h en cu st om ized (Fig 1). Specific t est ca ses a r e design ed t o su it t h e r equ ir em en t s a n d lin kin g t h em t o t h eir r espect ive r equ ir em en t (S ee T able
2). Th e design s of t h e specific t est ca ses a r e m a de by a ddin g t h e goa l of t h e
t est a lon g wit h t h e even t s t o a ch ieve t h e goa l. La st ly t h e expect ed r espon se is wr it t en , descr ibin g wh a t r esu lt s we sh ou ld expect by followin g t h e even t s. Th e wh ole pr ocess st a r t s by ca r efu lly ch eckin g a r equ ir em en t fr om t h e list a n d t r yin g t o see if t h ey ca n be m a de a s a sin gle t est ca se in on e go. If t h a t is n ot possible sever a l t est ca ses a r e n eed ed. If we look a t fir st r equ ir em en t in t a ble 1 a bove, we see t h a t 3 differ en t da t a t ypes n eed t o be t est ed. So we h a ve t o split t h e r equ ir em en t in t o m or e t h a n 1 t est ca se sin ce a ll P AT m a y n ot be a ble t o pr ocess a ll 3 da t a t ypes . We decide t o t a ke t h e fir st da t a t ype wh ich is for m et a bolom ic in pu t da t a . We a lso select a da t a in pu t t h a t we kn ow sh ou ld give a r espon se a n d pr esen t som e r esu lt s. F r om t h is we ca n wr it e down ou r even t s in t h e t est ca se by h a vin g a n in pu t a n d t h en get t in g a r espon se. So we ca n t h en a lso st a t e t h e expect ed r espon se. In ou r ca se it is t h a t t h e m et a bolom ic da t a t ype gives da t a in for m a t ion r ela t ed t o ou r da t a in pu t t h a t we m a de. N ext 2 t est ca ses will be sim ila r wit h t h e sm a ll differ en ce of h a vin g a differ en t in pu t da t a t ype. Sa m e a ppr oa ch m et h od is a pplied t o t h e r est of t h e t est ca ses. Requ ir em en t s a r e goin g t o be ch ecked, eva lu a t ed if it ca n be m a de a s on e t est or split t in g t h em in t o m or e t est ca ses for sa m e r equ ir em en t , wr it in g t h e even t s a n d t h e expect ed r espon se.
Ta b le 2. A t a ble sh owin g r equ ir em en t ID wit h descr ipt ion lin ked t o specific Test Ca se ID ID R e q u i re m e n t d e s c ri p t i o n Ty p e Li n k e d w i t h Te s t Ca s e ID
1 U ser is a ble t o see a n d select on t h e P AT wh a t t ype of da t a it m u st pr ocess (if t h e in pu t field is for m et a bolom ic, lipidom ic or gen om ic)
F u n c t i o n a l 1, 2 a n d 3 2 U ser m u st be a ble t o ch eck if t h e r esu lt s obt a in ed is va lid fr om t h e P AT a ccor din g t o lit er a t u r e or la bor a t or y r esu lt s N o n fu n c t i o n a l 4 3 Th e u ser m u st r eceive r esu lt s by t h e P AT wit h in a cer t a in t im e N o n fu n c t i o n a l 5 4 Th e u ser sh ou ld n a viga t e bet ween st a r t of sea r ch (in pu t da t a ) t o t h e en d of sea r ch (r esu lt s obt a in ed).
N o n
fu n c t i o n a l
6
5 Th e u ser sh ou ld get a visu a l pr esen t a t ion of m et a bolom ics, lipidom ics a n d gen om ics da t a fr om t h e P AT N o n fu n c t i o n a l 7 6 Th e u ser m u st be a ble t o zoom in a n d ou t expa n din g t h e view t o n eigh bor in g possible r esu lt s t o see con n ect ed pa t h wa ys on t h e r eceived r esu lt s fr om t h e P AT. F u n c t i o n a l 8 7 Th e u ser m u st in pu t a specific t ype of da t a in t o t h e P AT (m et a bolom ic, lipidom ic or gen om ic)
F u n c t i o n a l 9
8 Th e u ser m u st be a ble t o in pu t com bin ed om ics da t a a n d t h en m a p t h em t o pa t h wa ys
2.1.3. Objective
Th e m a in pu r pose is a ch ieved by a cqu ir in g kn owledge fr om lit er a t u r e su ch a s books a n d a r t icles a n d by doin g soft wa r e t est in g. Th e r esu lt s obt a in ed fr om t h e t est s a r e t h a n com pa r ed wit h r equ ir em en t s m a de by t h e pot en t ia l u ser s of t h e P AT.
2.1.4. U n d erlyin g objectives
Object ive 1:
Ga t h er in g of in for m a t ion by sea r ch in g books a n d a r t icles , fin din g lot s of P AT a n d obt a in wh a t da t a it ca n pr ocess . Down loa d P AT if possible t o a n a lyze t h em .
Object ive 2:
E va lu a t e t h e select ed P AT wit h t h eir fu n ct ion s a n d m et h ods by goin g t h r ou gh ea ch t ool, clickin g a r ou n d a n d in pu t t in g da t a . Test ca ses a r e design ed fr om t h e given r equ ir em en t s. Test s on t h e P AT a r e ba sed u pon :
a ) F r om t h e lit er a t u r e kn own m et a bolom ics, lipidom ics, a n d gen et ic pa t h wa ys a n d cor r ela t ion s
b) Com pa r ison bet ween r esu lt s obt a in ed fr om t h e lit er a t u r e a n d fr om t h e P AT
c) Com pa r ison bet ween exist in g la bor a t or y r esu lt s a n d t h e P AT d) H ow lon g it t a kes t o pr ocess da t a by t h e a n a lysis t ool
Cor r ect r esu lt s a r e con sider ed t o be t h ose t h a t com e fr om scien t ific a r t icles, books or la bor a t or y r esu lt s ver ified by scien t ist s. P a t h wa ys a n d cor r ela t ion s wit h m et a bolom ics, lipidom ics, a n d gen et ics a r e t est ed a ga in st lit er a t u r e kn own r esu lt s. Com pa r ison bet ween r esu lt s obt a in ed fr om P AT a ga in st a r t icle a n d book r esu lt s a r e goin g t o be don e fir st , a ft er wa r ds t h e exist in g la bor a t or y r esu lt s. Accu r a cy of t h e P AT a r e a cqu ir ed by t h e ou t pu t da t a a n d r esu lt s will eit h er a ccu r a t ely m a t ch a ll da t a or n ot . A sim ple t im er is u sed t o r ecor d t h e pr ocessin g t im e of a P AT. F in a lly a list of P AT will sh ow wh ich P AT pa ssed, fa iled a n d wh y t h ey fa iled ou r exa m in a t ion .
Object ive 3:
In or der t o h a ve a sa t isfied en d u ser , specific set of r equ ir em en t s a r e n eeded t h a t m u st be fu lfilled wit h a fin a l eva lu a t ion . Requ ir em en t s a r e collect ed a t a n ea r ly st a ge wit h in t er views fr om r esea r ch er s a n d t h e en d u ser wh o a lso r epr esen t ot h er pot en t ia l u ser s. Th e m ost desir ed a n d im por t a n t r equ ir em en t s wer e discu ssed a n d iden t ified t o be t h e followin g: Select ed a n a lysis t ool m u st be a ble t o:
a ) N a viga t e bet ween da t a a n d r esu lt s
b) Ma ke visu a l pr esen t a t ion of obt a in ed m et a bolom ics, lipidom ics or gen om ics da t a
c) H a ve zoom in a n d zoom ou t fu n ct ion s expa n din g t h e view t o n eigh bor in g possible r esu lt s con n ect ed t o pa t h wa ys on t h e r esu lt s obt a in ed
d) Th e P AT sh ou ld be a ble t o pr ocess m or e t h a n on e t ype of da t a (m et a bolom ic, lipidom ic or gen om ic)
e) Be a ble t o com bin e om ics da t a a n d t h en m a p t h eir pa t h wa ys N a viga t ion will be t est ed by lookin g a t t h e ou t pu t da t a (r esu lt s obt a in ed) t o t h e in goin g da t a (t h e begin n in g of wh er e da t a is in ser t ed). In ser t ion s of da t a a r e m a de in t h e r equ ir ed fields wh ile t r a cea bilit y or clicka ble t r a ckin g views a r e sou gh t wh en obt a in in g r esu lt s. An y visu a l pr esen t a t ion s on obt a in ed r esu lt s a r e a ccept ed bu t det a iled view of pa t h wa y com bin a t ion s a n d cor r ela t ion s a r e pr efer r ed. On ou t pu t da t a zoom fu n ct ion s a r e sou gh t t h a t is a sm a ll m a gn ifyin g gla ss wit h a plu s or m in u s sign in t h e P AT. To t est h ow m a n y t ype of da t a (m et a bolom ic, lipidom ic or gen om ic) t h e P AT ca n pr ocess, on e of ea ch da t a t ype will be select ed. Th r ee da t a t ypes t oget h er (m et a bolom ic, lipidom ic a n d gen om ic t oget h er ) a r e goin g t o be t est ed fir st , t wo da t a t ypes (m et a bolom ic wit h lipidom ic or gen om ic, lipidom ic wit h gen om ic or m et a bolom ic) a r e t est ed secon dly a n d la st ly on e by on e in pu t s of ea ch (m et a bolom ic, lipidom ic, gen om ic). If a P AT pa sses a ll a im s a ft er eva lu a t ion , a ll r esu lt s a n d t est m a t er ia l a r e in t en ded t o be t u r n ed over t o t h e en d u ser . F u r t h er su ppor t will be pr ovided in for m of a n swer in g qu est ion s on specific P AT. Test s on t h e P AT, U n ipr ot a n d F E vE R a r e goin g t o be don e if n o P AT will be fou n d t h a t fu lfill t h e r equ ir em en t s.
2.2.Alt e rn a t i v e re s e a rc h m e t h o d s
Th er e a r e a lt er n a t ive m et h ods t o con du ct t h is st u dy bu t it wou ld in volve wor k in g in a bioch em ist r y la bor a t or y t o obser ve, in t er view a n d obt a in r esu lt s fr om exper im en t s a n d a ft er wa r ds design in g wh ile a lso bu ildin g a com plet e P AT. An ot h er m et h od is t o m a ke a h om epa ge con n ect in g it t owa r ds a P AT t h a t is bein g u sed in t h e la bor a t or y. Met h od select ed in sect ion 3.1 a n d descr ibed m or e in sect ion 4 is bein g don e by r ea son s of get t in g good qu a lit y r esu lt s, t im e sa vin g a n d efficien cy.
3. Biom edica l ba ck gr ou n d
Th is sect ion con t a in s ba ckgr ou n d in for m a t ion n eeded in or der t o u n der st a n d t h e biom edica l pa r t . Ga t h er ed in for m a t ion is a bou t gen et ics, lipids a n d t h eir bioch em ist r y, m et a bolom ics, gen om ics a n d ca r d iova scu la r disea se.
3.1.Ge n e t i c s
Gen et ics is t h e st u dy of gen es wit h t h eir st r u ct u r es, sequ en ces a n d t h eir r ole in h er edit y. It is a wa y t o t r y a n d expla in h ow t h ey wor k, wh a t t h ey a r e a n d wh a t t h ey ca n do [32]. Gen et ics in volve scien t ific st u dies of gen es a n d t h eir effect s lea din g t o va r ia t ion in livin g or ga n ism s [32]. Mea n in g h ow cer t a in t r a it is or con dit ion s a r e bein g pa ssed down fr om on e gen er a t ion t o t h e n ext . Also h ow gen es a r e u n it is of h er edit y t h a t ca r r y in st r u ct ion s for m a kin g pr ot ein s
t h a t dir ect a ct ivit ies in cells a n d fu n ct ion s of ou r bodies. An exa m ple of fu n ct ion is in h er it ed disor der s lea din g t o disea ses [32]. Disor der s h a ve been det ect ed du e t o t h e la r ge a m ou n t of la bor a t or y exper im en t s a n d t ech n ology a dva n cem en t s, da t a st or in g pr ovide u se of P ATs, t h u s givin g fu n ct ion s t o sea r ch a n d m a t ch gen es wit h ea ch ot h er .
3.1.1. Gen e
Gen es a r e sm a ll m olecu la r u n it is t h a t ca r r y t h e h er edit y of livin g or ga n ism s. Th e gen e h olds t h e in for m a t ion t o bu ild a n d m a in t a in a n or ga n ism . E u ka r yot ic cells h a ve a n u cleu s, wh ich con t a in s t igh t ly pa cked DN A a n d a r e well pr ot ect ed [5]. Th e m a in bu ildin g blocks of a gen e con sist of cova len t ly lin ked n it r ogen ba ses A, T, C a n d G. Th e st r u ct u r es a r e t h en st r en gt h en ed by ca r bon a n d h ydr ogen bon ds. Th is m a kes a sequ en ce t h a t in t h e en d for m s a lon g dou ble h elix DN A ch a in . Th e DN A ch a in is t igh t ly pa cked t oget h er wit h h ist on es, wh ich a r e pr ot ein s, t o for m a n or ga n ized st r u ct u r e. Th e or ga n ized st r u ct u r e is ca lled ch r om osom es [11]. All t h e ch r om osom es a r e well pr ot ect ed wit h in t h e n u cleu s (Fig 2). Th e DN A ch a in in t u r n codes for m a n y fu n ct ion s of livin g or ga n ism s [5]. Gen et ic in for m a t ion a n d t r a it is a lso get s pa ssed on t o t h e offspr in g wh en m a t in g. In ou r gen om e t h er e a r e som e st r u ct u r a l gen es wh ich u pon r ea din g, t ell u s wh a t m a t er ia ls a r e n eeded in or der t o bu ild u p a cell or a n or ga n ism . Th is is ou r gen ot ype. Th e st r u ct u r a l gen es we a r e goin g t o u se a r e det er m in ed in com bin a t ion wit h t h e en vir on m en t a n d t h is is ca lled ou r ph en ot ype. Th e ph en ot ype is a lso a ffect ed by t h e en vir on m en t of ea r lier gen er a t ion s a n d t h is is ca lled epigen et ic [5]. Th ose ph en ot ypes a r e e.g. eye color a n d blood t ype. Th e gen ot ypes a r e iden t ica l in a ll h u m a n in dividu a ls u p t o a bou t 99 per cen t . Rem a in in g 1 per cen t va r y fr om per son t o per son cr ea t in g t h e fea t u r es t h a t m a kes u s a ll u n iqu e. Tin y differ en ces in t h e gen om e sequ en ces dist in gu ish a n in dividu a l fr om a n ot h er [5]. Th e t in y differ en ce on t h e ch a n ges of sin gle ba ses in volves r epr odu ct ion fr om t wo in dividu a ls cr ea t in g a n offspr in g a n d ch a n ges by Sin gle N u cleot ide P olym or ph ism (SN P ) a s m en t ion ed m or e in t ext below. Keepin g t r a ck of t in y differ en ces is h a r d a n d som e of t h ese t in y gen et ic va r ia t ion s a r e im por t a n t du e t o su scept ibilit y t o cer t a in disea ses (like a st h m a , dia bet es, scler osis a n d ca n cer ), u n less you h a ve a n a n a lysis t ool a t you r disposa l [5].
F i g u re 2. A sch em a t ic pr esen t a t ion of h u m a n DN A a ssem bled in t o a
ch r om osom e.
3.1.2. S N P
SN P is sh or t for Sin gle N u cleot ide P olym or ph ism a n d it is a sequ en ce va r ia t ion in DN A. Th is m ea n s t h a t a n it r ogen ba se is differ en t in a gen e sequ en ce for on e in dividu a l wh ile t h e r est of t h e gen e sequ en ce is st ill sim ila r t o a n ot h er in dividu a l [5]. F or a n exa m ple t h e gen e sequ en ce ATAGGC is a lm ost t h e sa m e a s t h e gen e sequ en ce ATCGGC, h owever , we h a ve a ch a n ge on t h e secon d A t o h a vin g a C in st ea d. Ch a n ges of on e n u cleot ide in t h e sequ en ce of ou r gen es a r e n a m ed Sin gle N u cleot ide P olym or ph ism (SN P ) a n d occu r t h r ou gh ou t t h e wh ole gen om e [3]. Sin gle N u cleot ide P olym or ph ism (SN P ) va r ia t ion s occu r in a ll species, lea din g t o gen et ic va r ia t ion s a n d m a y r esu lt in differ en t ph en ot ype of t h e or ga n ism . In [4] r esea r ch r esu lt s sh ow h ow differ en t ia t ion h a s occu r r ed. Th e gen et ic ch a n ges a r e ba sed on n a t u r a l select ion t o su it t h e m ost fa vor a ble a da pt ion of t h e gen es [3]. Som e of t h ese Sin gle N u cleot ide P olym or ph ism (SN P ) sequ en ces a r e even specific t o a n et h n ic gr ou p wh ile it m a y be m issin g in a n ot h er gr ou p. Accor din g t o [32] bot h t h e codin g a n d t h e n on codin g r egion s of t h e DN A ca n be a ffect ed. Sin gle N u cleot ide P olym or ph ism (SN P ) sequ en ces in volve su scept ibilit y t o disea ses a s m en t ion ed in t h e en d of sect ion 2.1.1. A scen a r io given will descr ibe wh y Sin gle N u cleot ide P olym or ph ism s (SN P : s) a r e im por t a n t [32]. Cou ples r egist er s for a h ea lt h ch eck a n d gives blood t o be a n a lyzed in or der t o det ect h ow h ea lt h y t h ey a r e. Th e blood goes t h r ou gh t r ea t m en t s so on ly sm a ll sequ en ces of n u cleot ides a r e left . Th e Sin gle N u cleot ide P olym or ph ism (SNP ) sequ en ce
of on e in dividu a l is t h e followin g:
ACGG”. Ot her person ha s t he following of
“GCCAGTATTGTCGATTTCACAAGTGCGTTTCTGTCGGGATGTCACACA
ACGG”. The sequences from bot h individual’s a re codes for a prot ein, coding t h e u pt a ke of fa t a n d su ga r in t h e h u m a n body. Th e sm a ll va r ia t ion s bet ween t h ese t wo in dividu a ls a r e m a r ked wit h a color . On e of t h em h a s h igh r isk of get t in g dia bet es. Wit h t h e h elp of t oda y’s t ech n ology, SNP a n a lyses a r e u sed t o det er m in a t e disea se su scept ibilit y [32]. An a lysis r evea ls t er r ible n ews for t h e cou ple, wer e t h e in dividu a l wit h t h e sin gle ba se ch a n ged t o G h a s t o st a r t u sin g in su lin wit h a syr in ge, u n less food h a bit ch a n ge wit h in a yea r or t wo. Th e scen a r io descr ibed a bove a r e ver y com m on in h ea lt h ca r e t oda y a n d a lso n ot t h e on ly wor k a r ea exploit in g gen et ic va r ia t ion s. In for en sic scien ce t h e gen et ic va r ia t ion s a r e exploit ed du r in g DN A fin ger pr in t in g [32].
3.2.B i o c h e m i s t ry o f Lip i d s
Bioch em ist r y is a lso ca lled biologica l ch em ist r y wh ich is t h e st u dy of ch em ica l pr ocesses in livin g or ga n ism s. Bioch em ist r y r egu la t es a n d gover n s over a ll livin g pr ocesses wit h in a ll livin g or ga n ism s [5]. Th is occu r s by bioch em ica l sign a lin g. Th e sign a lin g is sor t of a n in for m a t ion flow a s in sen din g a m essa ge fr om on e pla ce t o a n ot h er . Sign a ls flow t h r ou gh ever y pa r t in a n or ga n ism r egu la t in g t h e m et a bolism . Met a bolism st a n ds for t h e m ea n in g of livin g or ga n ism s t o su st a in life a n d r epr odu ce t h em s elf. On e im por t a n t pa r t in bioch em ist r y is t h e lipids. Lipids a r e im por t a n t com pon en t s in a cell a n d for m cell m em br a n e, vit a l t issu es a n d ser ve a s a n en er gy sou r ce for t h e or ga n ism [1]. Lipids a r e st or ed a s en er gy r eser ves wit h in t h e or ga n ism a n d u sed wh e n n eeded. Lipids h elp keepin g t h e elect r och em ica l ba la n ce of a cell, cell sign a lin g a n d t r a ffickin g r ega r din g wh a t is goin g in or ou t t o t h e cell [1 1]. Th e lipids u su a lly con sist of a pola r h ea d a n d a h ydr oph obic t a il. Th e lipids bin d t o ea ch ot h er du e t o t h e h ydr oph obic pa r t wa n t s t o st a y in con t a ct wit h ot h er h ydr oph obic m olecu les [3]. Th e dist r ibu t ion bet ween t h e h ydr oph obic a n d pola r pa r t s of t h e lipids dir ect s t h e 3 -dim en sion a l st r u ct u r e of t h e m olecu les [7] a n d wit h a r ela t ively la r ge pola r pa r t , t h e lipids for m m icelles wh ile m or e equ a l dist r ibu t ion , lea ds t o t h e for m a t ion of dou ble la yer s kn own a s m em br a n es (Fig 3).
F i g u re 3. P ict u r e of lipids wit h h ydr oph obic t a ils bou n d t oget h er a n d wit h
ot h er com pon en t s for m in g t h e m em br a n e. (Modified pict u r e t a ken fr om H u m a n Cell Biology r ef. [43]).
3.2.1. L ipid d efin ition
Ch em ist s, bioch em ist s a n d ot h er a n a lyst s t h a t wor k wit h lipids h a ve a gr ea t a n d fir m u n der st a n din g of t h e t er m ca lled lipid a ccor din g t o [19]. Bu t t h er e is n o widely a ccept ed defin it ion t oda y a n d t h ey a r e sa id t o be a gr ou p of n a t u r a lly occu r r in g com pou n ds. In a n or ga n ism , [44] a n d [53] st a t e t h a t t h ou sa n ds of va r iou s for m s of lipid m olecu les ca n be fou n d a n d lipids ca n be ca t egor ized in t o six m a in ca t egor ies (Fig 4). Th ey a ll h a ve a low solu bilit y in wa t er a n d h igh solu bilit y in or ga n ic solven t s.
3.2.2. Classes of L ipid s
Recen t ly a n ew n om en cla t u r e syst em wa s pr oposed by [26] du e t o t h e diver sit y of lipids in h u m a n pla sm a , sepa r a t in g lipids in t o eigh t cla sses or ca t egor y wh er e six of t h em a r e con sider e d m a in cla sses. E a ch cla ss ca n be fu r t h er divided in t o su b cla sses a n d in dividu a l m olecu la r species (Fig 3).
Th e fir st ca t egor y is t h e fa t t y a cyls a n d is a lso ca lled fa t t y a cids. Th e fa t t y a cids ca n h a ve t h r ee for m s su ch a s fa t t y a cids, oct a deca n oids a n d eicosa n oids. Th ey a r e t h e m ost com m on bu ildin g block for m or e st r u ct u r a l com plex lipids a n d ca n be sa t u r a t ed or u n sa t u r a t ed. Cells u se t h ese lipids t o for m t h e va r iou s m em br a n es fou n d in a cell, t o st or e en er gy a n d t o a dju st t h e m em br a n e flu idit y in m a n y ce lls. [43, 53]
Secon d ca t egor y is t h e Glycer olipids a n d h a s t h r ee for m s a s m on o-, di- a n d t r ia cylglycer olipids. Th eir fu n ct ion s a r e m a in ly a s en er gy st or a ge a n d a r e bu lked u p in t h e t issu e a s fa t in a n im a ls. [43, 53]
Th ir d ca t egor y is ca lled Glycer oph ospolipids bu t t h ey a r e u su a lly ca lled ph osph olipids. Th e m a in for m s a r e P h osph a t idylch olin e (P C), P h osph a t idylch et h a n ola m in e (P E ) a n d P h osph a t idic a cid (P A). Th e glycer oph ospolipid cla sses a r e t h e on ly on es t h a t h a ve a ph osph or bin din g a n d t h ey a r e t h e key com p on en t in or der t o for m bila yer s. [43, 53]
Th e fou r t h ca t egor y con sist s of Sph in golipids. Th e m a in for m s a r e Sph in gom yelin a n d Cer a m ides. Th e Sph in golipids h a ve a pola r h ea d a n d t wo n on pola r t a ils. Sph in gom yelin a ct a s a pr ot ect ion for m in g a m yelin sh ea t h t o pr ot ect n er ves. [43, 53]
Th e fift h ca t egor y is t h e St er ol lipids a n d t h ey a r e of va r iou s a lcoh ol for m s. St er ol lipids a r e a n im por t a n t com pon en t for biologica l r oles. St er ols a ct a s r egu la t in g h or m on es a n d a s sign a lin g m olecu les. [43, 53]
Th e la st ca t egor y is t h e P r en ols t h a t for m t er pen es a n d a ct a s a pr e -cu r sor m ole-cu les of vit a m in s a s vit a m in A, E a n d K. [43, 53]
3.2.3. E n zym es in volved in th e syn th esis of lipid s
A deeper in sigh t is pr esen t ed in t h is sect ion wit h focu s on lipids a n d it is syn t h esis, for a m or e u n der st a n din g on t h e a m ou n t of in for m a t ion a P AT m u st be a ble t o pr ocess. St a r t in g fr om t h e st a r t of da t a in pu t s (a lipid n a m e con n ect ed t o glycer olipids) t o r esu lt s obt a in ed.
Som e lipid ch a in s a r e ver y lon g or com plex wh ile ot h er s a r e sh or t . It wou ld t a ke a lon g t im e t o ch em ica lly syn t h esize t h e lipids, h owever , wit h t h e h elp of en zym es it is m u ch fa st er a s [37] pr esen t s. N u m er ou s for m s of lipids occu r a n d sever a l en zym es a r e n eeded. In [46] a syst em biology view pr esen t s n eeded en zym es by u se of a P AT. E .g. t h e syn t h esis of fa t t y a cids occu r s in t h e cyt opla sm a n d key en zym es in volved a r e t h e a cet yl -CoA ca r boxyla se (ACC) a n d m a lon yl-CoA ca r boxyla se (MCC) st a t ed in [51]. Wh ile a n ot h er gr ou p of coen zym e ca lled Acyl-CoA, ch or est er ol a cylt r a n sfer a se (ACAT) wor ks on ch olest er ol [51]. Th is is st r en gt h en ed in [45] sh owin g a clea r view by pict u r es. Th e fa t t y a cids a r e so m a n y a n d ca n be sa t u r a t ed or u n sa t u r a t ed a n d for t h is pu r pose design a t ed sym bols a r e given [31] in or der t o keep t r a ck of t h e ca r bon a t om s a n d t h eir bin din gs. Th e sym bols con sist of t wo n u m ber s bet ween a colon (:) [31]. Th e fir st n u m ber t ells u s t h e ca r bon len gt h of t h e fa t t y a cid a n d t h e secon d n u m ber t h e st a t e of sa t u r a t ion . A fa t t y a cid wit h sever a l u n sa t u r a t ed bou n ds sh ows a h igh er n u m ber a t it is secon d va lu e (S ee T able 3). Syn t h esis of fa t t y a cids beyon d 16 ca r bon s len gt h goes t h r ou gh a t wo-ca r bon elon ga t ion pr ocess, a ccor din g t o [31] by en zym es in t h e en dopla sm ic r et icu lu m (E R). N ot on ly elon ga t ion occu r s bu t a lso desa t u r a t ion by en zym es in t h e en dopla sm ic r et icu lu m (E R) u sin g fou r en zym es n a m ed desa t u r a se delt a fou r , delt a five, delt a six a n d delt a n in e. Th e design a t ed delt a n a m es wit h a n u m ber a r e given a ccor din g t o wh ich posit ion in t h e fa t t y a cid ca r bon ch a in t h e desa t u r a t ion occu r s [31]. Th e m a in den a t u r a se is delt a n in e a n d is ca lled St ea r oyl-CoA desa t u r a se-1. Th e desa t u r a t ion r equ ir es oxygen (O2), a coen zym e ca lled N icot in a m ide a den in e din u cleot ide h ydr ogen (N ADH ) a n d
a n elect r on t r a n spor t in g h em opr ot ein ca lled Cyt och r om e b5 [47]. In fa t t y a cid desa t u r a t ion t wo h ydr ogen a t om s a r e r em oved fr om t h e fa t t y a cid m a kin g a n oxida t ion on bot h t h e fa t t y a cid a n d N ADH . Th is cr ea t es a dou ble bon d bet ween ca r bon s in t h e fa t t y a cid ch a in .
Ta b le 3. Th e m a in fa t t y a cids in or ga n ism s (Modified t a ble t a ken fr om Cyber lipid
cen t er r ef. [31] a n d Vir gin ia web edu ca t ion r ef. [10])
Main fatty acids
Number of
carbons
Name Systematic name Symbol Structure
Saturated fatty acids
12 Lauric acid Dodecanoid acid 12:0 CH3( CH2)10COOH
14 Myristic acid Tetradecanoic acid 14:0 CH3( CH2)12COOH
16 Palmitic acid Hexadecanoic acid 16:0 CH3( CH2)14COOH
18 Stearic acid Octadecanoic acid 18:0 CH3( CH2)16COOH
20 Archidic acid Eicosanoic acid 20:0 CH3( CH2)18COOH
22 Behenic acid Docosanoic acid 22:0 CH3( CH2)20COOH
24 Lignoceric acid Tetracosanoic acid 24:0 CH3( CH2)22COOH
Unsaturated fatty acids
16 Palmitoleic acid 9-Hexadecanoic acid 16:1 CH3( CH2)5CH=CH(CH2)7COOH
18 Oleic acid 9-Octadecanoic acid 18:1 CH3( CH2)7CH=CH(CH2)7COOH
18 Linoleic acid 9,12-Octadecanoic acid
18:2 CH3(CH2)4(CH=CHCH2)2(CH2)6COOH
18 a-Linolenic acid 9,12,15-Octadecanoic acid
18:3 CH3CH2(CH=CHCH2)3(CH2)6COOH
18 g-Linolenic acid 6,9,12-Octadecanoic acid
18:3 CH3(CH2)4(CH=CHCH2)3(CH2)3COOH
20 Arachidonic acid
5,8,11,14-Eicosatetraenoic acid
20:4 CH3(CH2)4(CH=CHCH2)4(CH2)2COOH
24 Nervonic acid 15-Tetracosanoic acid 24:1 CH3(CH2)7CH=CH(CH2)13COOH
Com plex lipids h a ve a lon ger biosyn t h et ic pa t h wa y a n d t wo m a in pa t h wa ys a r e kn own a ccor din g t o [47], t h e sn -glycer ol-3-ph osph a t e pa t h wa y (a lso kn own a s t h e Ken n edy pa t h wa y) a n d t h e m on oa cylglycer ol pa t h wa y (Fig. 5
an d 6). Syn t h esis by t h e Ken n edy pa t h wa y occu r s in t h e liver a n d a dipose
t issu es wh ile t h e m on oa cylglycer ol pa t h wa y t a kes pla ce in in t est in e con fir m ed in [42]. Bot h st a r t s by ca t a bolism of glu cose (glycolysis) r esu lt in g in t h e bio-syn t h esis of glycer ol, h owever , n ew eviden ce in [47] in dica t es som e glycer ol is syn t h esized a n ew (de n ovo) fr om sin gle m olecu les by a pr ocess ca lled glycer on eogen esis. Th e followin g r ea ct ion s occu r in t h e
en dopla sm ic r et icu lu m (E R) of m a m m a lia n or ga n ism s [47]; sn -glycer ol-3-ph osol-3-ph a t eis est er ified by a fa t t y a cid coen zym e in a ca t a lyt ic r ea ct ion by t h e en zym e glycer ol-3-ph osph a t e a cylt r a n sfer a se (GP AT) a t t h e sn - posit ion in or der t o for m lysoph os ph a t idic a cid. Lysoph osph a t idic a cid t h en becom es a cyla t ed for m in g ph osph a t idic a cid, a n in t er m edia t e pr odu ct in t h e syn t h esis of a ll glycer olipids [47]. Du r in g syn t h esis of t r ia cyl-sn -glycer ol t h e ph osph a t e gr ou p is r em oved by a fa m ily of en zym es ca lled l ipid ph osph a t e ph osph a t a se (P AP ), st a t ed by [47], for m in g 1,2-dia cyl-sn -glycer ols a n d fu r t h er a cyla t ed by dia cylglycer ol a cylt r a n sfer a se (DGAT) in t o t r ia cyl sn -glycer ol (Fig 5). Du r in g syn t h esis of glycer oph ospolipids, ph osph a t idylch olin e (P C), ph osph a t idylch et h a n ola m in e (P E ) a n d ph osph a t idylser in , t h e ph osph a t e gr ou p is n ot r em oved st a t ed by [6] fr om ph osph a t ic a cid. In st ea d ph osph a t ic a cid a r e u sed a s pr e -cu r sor m olecu les in t h e syn t h esis of glycer olipids (Fig 6). Th e syn t h esis by t h e m on oa cylglycer ol pa t h wa y is less com plex a n d in volves on ly a few en zym es belon gin g t o a n a cylglycer ol a cylt r a n sfer a se fa m ily t o for m t h e t r ia cylglycer ols in t h e in t est in e [47].
F i g u re 4. Seven lipid cla sses a n d h ow t h ey in t er a ct bio-syn t h et ica lly (Modified
pict u r e t a ken fr om Molecu la r bioch em ist r y r ef. [45]).
F i g u re 5. Th e Ken n edy pa t h wa y syn t h esis in m a m m a ls (Modified pict u r e t a ken
F i g u re 6. Syn t h esis of a cylglyer ides a n d glycer oph osph olipids sh owin g a lin k
bet ween t h e t wo pa t h wa ys (Modified pict u r e t a ken fr om Lipid Libr a r y r ef. [35]).
3.2.4. L ipoprotein s
Lipids a r e a lm ost in solu ble, h owever , t h er e a r e wa ys for t h em t o be t r a n spor t ed or pa ss t h r ou gh t h e blood cir cu la t ion [5]. Lipopr ot ein s a llow t h e lipids t o be t r a n spor t ed t h r ou gh t h e blood cir cu la t ion in or der t o r ea ch differ en t t issu es [5]. Th e lipopr ot ein s a r e a ssem bled in a wa y t h a t it con t a in s bot h pr ot ein s a n d lipids. Th e pr ot ein pa r t ser ves a s a n em u lsifica t ion for t h e lipids [11] a n d t h er e a r e five m a jor cla sses, t wo bein g ver y im por t a n t cla sses of t h e lipopr ot ein s [1], h igh den sit y lipopr ot ein s (H DL) a n d low den sit y lipopr ot ein s (LDL). Rem a in in g lipopr ot ein s a r e In t er m edia t e den sit y lipopr ot ein (IDL), ver y low den sit y lipopr ot ein s (VLDL) a n d ch ylom icr on s [11]. Bot h H DL a n d LDL ca r r y lipids a s ch olest er ol a n d LDL is som et im es r efer r ed t o a s t h e ba d ch olest er ol wh ile H DL is t h e good ch olest er ol. P r oblem s ca n occu r du r in g t h e oxida t ion of t h e LDL a ccor din g t o [11], lea din g t o a lm ost u n st oppa ble ch a in r ea ct ion s. Ch a in r ea ct ion effect r esu lt s in a t h er oscler osis m a n y yea r s la t er [1 1].
3.3.Ge n o m i c s
Gen om ics is a disciplin e wit h in gen et ics t h a t focu s on t h e st u dy of t h e gen om e of a ll or ga n ism s [32]. Wit h in t h is field of r esea r ch t h e pu r pose is t o det er m in e t h e en t ir e DN A sequ en ce of a ll or ga n ism s a n d m a kin g a sca led m a ppin g of a ll t h e gen es [32]. Th is in clu des a lso m a ppin g of wh a t a gen e does a n d t h e a ssocia t ion it h a s t o pr ocesses wit h in a n or ga n ism e.g. m et a bolom ics or lipidom ics [7]. Du r in g t h e pr ocess of m a ppin g a n d a ssocia t ion ea ch gen e get s a design a t ed n a m e a n d n u m ber (a s a n ID t a g) wit h a ll t h e n ecessa r y in for m a t ion pr ovided a bou t t h a t specific gen e in a da t a ba se [32]. In for m a t ion ca n be r et r ieved wit h a P AT fr om t h ese da t a ba ses wh en n eeded.
3.4.Me t a b o lo m i c s
Met a bolom ics is t h e st u dy of ch em ica l pr ocesses in volvin g m et a bolit es a n d soph ist ica t ed a n a lyt ica l t ech n ologies a r e u sed t o m a ke syst em a t ic st u dies [8, 18]. A syst em a t ic st u dy con sist s of t a r get a n a lysis, m et a bolit e pr ofilin g a n d m et a bolic fin ger pr in t in g. Th e m et a bolit es a r e fou n d in a ll biologica l cells a n d a ll h a ve u n iqu e ch em ica l sign a t u r es, like a fin ger pr in t [46]. Th e u n iqu e fin ger pr in t s a r e a n en d pr odu ct a ft er a cellu la r pr ocess a n d ca n be u sed t o see h ow specific ch em ica l pr ocesses h a ve occu r r ed [8, 46]. Th e ch em ica l pr ocesses t h a t a r e exa m in ed ca n be fr om a livin g or ga n ism , cells, t issu es a n d even fr om a n or ga n . Resea r ch field of m et a bolom ics con sist s of m a n y su b pa r t s a n d t h e pa r t s we a r e focu sin g on a r e t h e st u dy of lipidom ics (lipids/fa t t y a cids) [40].
3.5.Li p i d o m i c s
Lipidom ics is u sed for descr ibin g t h e com plet e pr ofile of lipids in cells, t issu es or or ga n ism s [47]. Lipidom ics a r e on e su bpa r t of m et a bolom ics a n d a n ewly em er ged r esea r ch field t h a t h a s been dr iven fa st for wa r d by r a pid a dva n ces in t ech n ology [53]. Su ch t ech n ologies a r e e.g. m a ss spect r om et r y (MS), flu or escen ce spect r oscopy (F S) [24], a n d Nu clea r Ma gn et ic Reson a n ce (N MR) [39]. Th ese t ech n ologies sa ve la r ge a m ou n t s of da t a in da t a ba ses, givin g P AT's possibilit y of a n ew m et h od for da t a a n a lysis [18].
3.6.Ca rd i o v a s c u la r d i s e a s e s
Th er e a r e m a n y disea ses a r ou n d t h e wor ld. On e of t h em is a cla ss of disea ses t h a t in volve h ea r t or vessels t h a t t r a n spor t s blood (a r t er ies a n d vein s) a n d a r e ca lled ca r diova scu la r disea ses [46]. Ca r diova scu la r disea ses in clu de t h e followin g: An eu r ysm (Abn or m a l bu lge in a n a r t er y), An gin a (Ch est pa in du e t o la ck of blood t o t h e h ea r t m u scle), At h er oscler osis (pla qu e bu ilds u p in side t h e a r t er ies), Cer ebr ova scu la r Acciden t (St r oke), Con gest ive H ea r t F a ilu r e, Cor on a r y Ar t er y Disea se a n d Myoca r dia l In fa r ct ion (H ea r t At t a ck). Sever a l r esea r ch er s in [12] cla im som e kn own fa ct or s a s lipid or fa t con t en t ca n a ffect t h e ca r diova scu la r syst em , poin t in g t h a t h igh den sit y lipopr ot ein s (H DL) a n d low den sit y lipopr ot ein s (LDL) a r e r ega r ded t o be a fa ct or beh in d t h e ca r diova scu la r disea ses. On ce t h e disea se is det ect ed it h a s u su a lly pr ogr essed for yea r s a n d lea ds t o t h e n ecessit y of oper a t ion or even dea t h . An ot h er gr ou p of r esea r ch er s in [29] h a ve sh own t h a t t h er e a r e sever a l SNP :s wh ich is a ssocia t ed wit h pla sm a level of h igh den sit y lipopr ot ein s (H DL) a n d low den sit y lipopr ot ein s (LDL) wh ich a r e a ssocia t ed wit h m yoca r dia l in fa r ct ion . Aft er t est in g in dividu a ls in [2], fr om five differ en t et h n ic gr ou ps wit h r espect of eigh t SN P fr om t h r ee gen es a ssocia t ed wit h ch olest er ol a n d lipopr ot ein syn t h esis, a clea r cor r ela t ion wit h m yoca r dia l in fa r ct ion s wa s obt a in ed. A st u dy on r isks for m yoca r dia l in fa r ct ion in [48] st r en gt h en s t h is t h eor y.
4. Com pu t er Scien ce ba ck gr ou n d
Th is sect ion con t a in s ba ckgr ou n d in for m a t ion n eeded in or der t o u n der st a n d t h e IT pa r t a n d h ow a P AT wor ks.
4.1.D a t a b a s e s , D a t a m i n i n g a n d Kn o w le d g e d i s c o v e ry
A da t a ba se con sist s of t a bles wit h m a n y colu m n s a n d r ows wit h a collect ion of va st a m ou n t of da t a in for m of in for m a t ion . Th e in for m a t ion is st or ed a t a specific pla ce a n d is oft en bein g well or ga n ized. Wit h in t h e da t a ba se depen din g on wh a t is in ser t ed in t o it , t h e in for m a t ion ca n be of gen et ics, lipidom ics or a bou t som et h in g else en t ir ely. Da t a ba ses oft en r equ ir e som e for m of t ool in or der t o r ea d a n d r et r ieve specific in for m a t ion fa st a m on g t h e va st a m ou n t of da t a . Th is is wh er e da t a m in in g com es in , wh en specific in for m a t ion is sou gh t a n d ga t h er ed by a t ool, t h en pr esen t ed a s r esu lt s. F r om t h e pr esen t ed r esu lt s, kn owledge ca n be ga in ed . Th e ga in ed kn owledge h a ve m a n y for m s bu t a few of t h ese ca n per h a ps be t o m a ke im pr ovem en t in exper im en t s, con fir m in g exper im en t r esu lt s or per h a ps ch a n ge a ppr oa ch m et h ods t o solve a scien t ific pr oblem [13].
4.2.P AT
As m en t ion ed ea r lier a ll kin ds of IT-ba sed t ools h a ve been developed in va r iou s biom edica l fields [21]. Th is h a s been don e in or der t o keep t r a ck of a ll t h e n ecessa r y scien t ific in for m a t ion obt a in ed du r in g t h e pa st yea r s [20]. P AT t h a t we a r e wor kin g wit h pr ocess in for m a t ion a bou t gen es, SNP :s a n d lipid m et a bolism . Th er efor e t h e P AT pla y a n im por t a n t r ole in lipidom ics a n d gen om ics r esea r ch . Th e t ools ca n be eit h er web ba sed soft wa r e or down loa da ble pr ogr a m s t h a t t a ke da t a in for m s of a gen e n a m e, SNP a ccession ID (r s n u m ber ) or a cla ss n a m e of t h e lipid. Th e P AT t h en pr ocess t h e da t a given , m a kin g sea r ch es in loca l or r em ot e da t a ba ses. Th e da t a ba ses con sist s of m a n y t a bles wit h differ en t in for m a t ion r ela t ed t o gen es a n d lipids. Wh a t t h e P AT do is m a kin g m a n y join fu n ct ion s bet ween t h e t a bles a n d pu t t h ese in for m a t ion t oget h er . Wh en a sea r ch occu r s by da t a m in in g, t h e in for m a t ion fr om t h ese t a bles a r e ga t h er ed a n d pr esen t ed a s r esu lt s ba sed on t h e in pu t pa r a m et er s [9]. Th e in pu t pa r a m et er s a r e t h e in ser t ed t ext s in t h e sea r ch field. In som e ca ses t h e t ools fa il t o pr ovide r esu lt s on cer t a in in pu t . F in a lly t h e a n a lysis t ool sh ows t h e r esu lt s t ellin g if a n y r esu lt s wer e fou n d, wh er e t h e lipids or gen es a r e u sed in t h e m et a bolism a n d h ow t h ey a r e con n ect ed t o ot h er lipids or gen es in t h e m et a bolism . Th e r esea r ch er s wor kin g wit h t h e P AT ca n fu r t h er a n a lyze t h e r esu lt s in or der t o ga in n ew kn owledge. Wit h n ew kn owledge, n ew discover ies ca n be m a de in e.g. lipidom ics or gen om ics a n d t h is lea ds t o t h e dem a n d for u pda t es t o t h e da t a ba ses a n d t h e P ATs (Fig 8). Wit h t h e h elp of P AT, n ew d iscover ies of disea ses like a t h er oscler osis ca n be m a de [24] or n ew pa t h wa y lin k s in t h e m et a bolic syst em r espon ses ca n be fou n d [52].
F i g u re 8. A view on h ow ever yt h in g is con n ect ed (bot h vir t u a lly a n d
ph ysica lly) t o t h e P AT.
5. Requ ir em en t s a n d Test elicit a t ion
Th e followin g sect ion con t a in s in for m a t ion a bou t r equ ir em en t specifica t ion , t est pla n , t est ca se, a n d soft wa r e t est in g.
5.1.R e q u i re m e n t s
Ma n y soft wa r e pr ogr a m s or t ools r equ ir e m on t h s of t est in g t o see if t h ey fu n ct ion cor r ect ly a n d n eed ver y t h or ou gh set s of specific r equ ir em en t s in or der t o be con sider ed a s good fu n ct ion a l t ools, a s st a t ed in [39]. Specific set s of r equ ir em en t s ca n be obt a in ed by in t er views wit h t h e people wh o a r e of im por t a n ce su ch a s st a keh older s or in dividu a ls wit h a key r ole. We u se a n em pir ica l m et h od on soft wa r e t est in g by ga t h er in g r equ ir em en t s pa r t ia lly ba sed on a r equ ir em en t s ph a se fr om on e of t h e wa t er fa ll m odels u sed by Ia n Som m er ville [50]. In t h e r equ ir em en t s ph a se, som et im es a lso ca lled r equ ir em en t s en gin eer in g ph a se, br a in st or m in g, r esea r ch a n d a n a lysis is bein g con du ct ed on t h e soft wa r e t h a t will eit h er be developed or t est ed. We in t en d t o do t h e t est in g pa r t wit h ou t developin g a n y n ew P AT a n d t h er efor e on ly t h e r equ ir em en t s m et h odology is a da pt ed a n d a pplied in ou r st u dy. Th e br a in st or m in g, r esea r ch a n d a n a lysis is t h e m ost im por t a n t pa r t of r equ ir em en t s ga t h er in g. Ba sic r equ ir em en t s a r e defin ed a n d set for u ses t h a t t h e soft wa r e m u st su ppor t [49]. Du r in g t h is ph a se, in -dept h st u dies of cu r r en t wor kin g pr ocesses a r e don e a n d h ow t h e pr oblem s ca n be a ddr essed or solved. Th u s, wit h ou t u n der st a n din g t h e r equ ir em en t s given , h opes of deliver in g a
su ccessfu l syst em or soft wa r e is u n likely. Requ ir em en t s elicit a t ion s a r e don e in volvin g m a n y in t er views wit h key in dividu a ls. Requ ir em en t s a r e a n a lyzed a n d eva lu a t ed a n d ca n be of t h r ee kin ds. Th ose wit h h igh est pr ior it y a r e t h e
m u st h ave, secon d pr ior it y a r e sh ou ld h ave a n d t h e lowest pr ior it y a r e t h e n ice to h ave. Specifica t ion s a r e t h en m a de t o t h e r equ ir em en t s a n d va lida t ion s a r e
don e wh er e t h e in dividu a ls wit h a key r ole or st a keh older s a ccept t h e r equ ir em en t s. Requ ir em en t s a r e t h er efor e n eeded in or der t o defin e wh a t a soft wa r e pr ogr a m m u st or sh ou ld do, fea t u r es it h a s a n d a cer t a in qu a lit y t h a t it m u st fu lfill [39]. Requ ir em en t s a r e divided in t o fu n ct ion a l a n d n on fu n ct ion a l r equ ir em en t s. F u n ct ion a l r equ ir em en t s a r e a lwa ys defin ed wit h sh a ll or m u st . N on fu n ct ion a l r equ ir em en t s a r e pr oper t ies or cer t a in qu a lit ies a pr odu ct m u st h a ve a n d a r e u sed t o descr ibe soft wa r e’s u sa bilit y, r elia bilit y a n d per for m a n ce [17]. Qu a lit y is n ot som et h in g t h a t ca n be m ea su r ed ea sily a s m en t ion ed in sect ion 1.3, bu t on e wa y t o m ea su r e qu a lit y a ccor din g t o [23] is by u sin g m et r ics or st a t ist ics on pr oper t ies t h a t ca n be m ea su r ed a n d t h a t a r e a ssocia t ed wit h qu a lit y.
5.2.Te s t i n g
In or der t o do good t est in g, t est pla n s a r e developed in t h e for m of a docu m en t so t h a t syst em a t ic a ppr oa ch es ca n be u sed on soft wa r e t est in g. Th e syst em a t ic a ppr oa ch es a r e fa st a n d t im e sa vin g [30]. A t est pla n descr ibes t h e t est in g ph a ses (e.g. u n it t est in g, in t egr a t ion t est in g, a ccept a n ce t est in g), t h e n eeded r equ ir em en t s, a ll a ct ivit ies, t h e n eeded r esou r ces a n d t h e docu m en t a t ion n ot es. In t h is wor k, we u se a ccept a n ce t est in g t o det er m in e if a set of r equ ir em en t s will be m et . Th e a ccept a n ce t est in g is r u n n in g wit h specific da t a . On ce t h e r esu lt s a r e obt a in ed, t h ey a r e com pa r ed wit h kn own expect ed r esu lt s. U pon cor r ect m a t ch of t h e r esu lt , a pa ss or n o pa ss is given . Th er e a r e m a n y wa ys t o m a ke t est s a n d m ost of t h e t im e t h ey differ bet ween com pa n ies [30]. All t est pla n s a r e cr ea t ed pr ior t o a n y t est in g. Th e con t en t of a t est pla n u su a lly con sist s of a su it a ble n a m e r ela t ed t o t h e t est s per for m ed. On ce a t est pla n is select ed, it is per for m ed a ccor din g t o a t em pla t e [30] wh er e t h e t est pla n docu m en t is divided in t o t wo pa r t s. Th e fir st pa r t con sist s of gen er a l in for m a t ion a bou t t h e t est s t h a t will be per for m ed . Th e gen er a l in for m a t ion con t a in s pa r t icipa n t s, t est st r a t egies, specifica t ion s a n d fu n ct ion s or fea t u r es t h a t will be u sed. Th e secon d pa r t con t a in s t h e pr ocedu r e on scen a r ios a lso ca lled ca ses on h ow t est s will be don e. Th e cr ea t ion of t h e t est pla n , r equ ir em en t s a n d t est ca ses will lea d t o t h e a ct u a l soft wa r e t est in g. Th e pu r pose of t h e soft wa r e t est in g is t o in vest iga t e a n d ga in in for m a t ion on h ow t h e select ed soft wa r e pr ogr a m wor k s [39]. Soft wa r e pr oper t ies a r e eva lu a t ed du r in g a select ed soft wa r e t est in g. Du r in g t h e soft wa r e t est in g, b u gs a n d er r or s t h a t m igh t occu r a r e a lso elim in a t ed [23]. On ce t h e soft wa r e pr ogr a m or a pplica t ion m eet s t h e r equ ir em en t s, it is con sider ed t o be wor k in g well a n d a lso sa t isfies t h e n eeds of t h ose wh o r equ est ed it .
5.3.Te s t c a s e s
A set of t est con dit ion s h a ve t o be wr it t en fr om fu n ct ion a l r equ ir em en t s [17] if soft wa r e is goin g t o be t est ed. Th e t est con dit ion s a r e r efer r ed t o a s t est ca ses a n d a r e per for m ed in cer t a in sequ en ces wh ich it m u st follow du r in g t est in g. F ir st t h e goa l of t h e t est is descr ibed wit h t h e even t or execu t ion st eps, followed by t h e expect ed r es pon se a n d t h e a ct u a l r espon se fr om t h e t est . Ma n y t im es t est ca ses a r e cr ea t ed, wit h a set of con dit ion s fr om given r equ ir em en t s a s m en t ion ed a bove, in or der t o elim in a t e t h e a m bigu it y t o t h e m in im u m in soft wa r e [21]. Th e a m ou n t of t est ca ses depen ds on t h e a m ou n t of r equ ir em en t s given . To per for m t h e t est in g ph a se, t est er s a r e select ed t o exa m in e, discover a n d det er m in e if t h e soft wa r e is wor kin g cor r ect ly or n ot du r in g t est in g. To keep t r a ck of a t est er 's wor k t r a cea bilit y m a t r ices a r e u sed, lin kin g r equ ir em en t s t o specific t est ca ses (Fig 8). A t est ca se con sist s of m a n y st eps st a r t in g wit h a n in pu t ba sed on a r equ ir em en t t h a t will be t est ed a n d en din g on ce a ll st eps h a ve been com plet ed. Th e a ct ion or execu t ion even t s a r e t h en goin g t o be m a de on h ow t o do t h e t est wit h descr ipt ion s on expect ed r espon se or ou t com e. Th e a ct u a l r esu lt s obt a in ed will be wr it t en down on ce t h e t est ca se is com plet e.
F i g u re 1. A t est ca se t em pla t e u sed in t h is st u dy.
6. Resu lt
6.1.F i n d i n g t h e P ATs
Wit h u se of In t er n et , sea r ch in g for P ATs, m a n y wer e fou n d a n d m ost of t h em h a d t h eir own h om epa ges. Sea r ch es wit h t h e Google sea r ch en gin e wer e m a de a s “P AT”. 46 hom epages were found, descr ibing a nalysis t ools tha t ha d t o be eva lu a t ed. Th e h om epa ges st a t ed wh a t t ype of da t a t h e P ATs cou ld pr ocess, wh ich wa s con fir m ed by down loa din g a n d t est in g t h e P ATs. Th e down loa ded P ATs wer e eva lu a t ed wit h t est ca ses 1 t o 3 t h a t r equ ir e t h e t ool t o be a ble t o
