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Monte karlo metode I primene u bioinformatici master rad
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səhifə | 11/11 | tarix | 17.11.2018 | ölçüsü | 1,03 Mb. | | #81043 |
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6. ZAKLJUČAK
Monte Karlo metode su veoma široka oblast matematike. One nam putem simulacija i korišćenjem slučajnih brojeva daju dosta dobre aproksimacije nekih veoma teških problema. U ovom radu smo predstavili neke od najpoznatijih i najkorišćenijih Monte Karlo metoda, kao i primenu na problem uvijanja proteina, mada treba naglasiti da ove metode imaju veoma značajnu ulogu u rešavanju problema i u drugim oblastima i naukama. Prednost Monte Karlo metode, za razliku od molekulske dinamike, je to što ona nije ograničena Njutnovim jednačinama kretanja, pa poseduje veću slobodu pri predlaganju narednih pokreta radi generisanja novih konformacija. Različiti pokreti se mogu kombinovati radi postizanja veće fleksibilnosti simulacija koje se mogu na jednostavan način paralelno izvršavati na više računara. Monte Karlo simulacije ne pokazuju samo šta će se dogoditi već i koliko je verovatan svaki od tih ishoda, a pored toga obezbeđuju i grafički prikaz radi lakse analize i tumačenja dobijenih rezultata.
Nedostatak Monte Karlo metode je to što ona zahteva generisanje velikog broja uzoraka, što iziskuje dosta vremena i resursa. Takođe, je potrebno generisati sve uslove i ograničenja relevantna za rešavanje posmatranog problema, a pošto se proces zasniva na pokušajima i pogreškama simulacija ne predstavlja uvek optimalno rešenje. Pošto Monte Karlo metode ne rešavaju Njutnove jednačine kretanja one zato ne obezbeđuju nikakve dinamičke informacije. Jedna od glavnih problema Monte Karlo simulacije proteina u eksplicitnom rastvaraču jesu veliki koraci koji značajno menjaju unutrašnje koordinate proteina bez pomeranja rastvarača, što u velikom broju slučajeva dovodi do preklapanja atoma, a samim tim i odbacivanja posmatrane konformacije. Simulacija proteina u implicitnom rastvaraču15 nema ovaj problem, pa je za nju pogodnije koristiti Monte Karlo metode. Takođe, ne postoji opšti program koji se koristi za MK simulaciju protenina zbog toga što odabir pokreta koji će se koristiti i njihova stopa prihvatanja varira u zavisnosti od problema koji rešavamo. Nedavno je Monte Karlo modul dodat u CHARMM softver za simulaciju [42].
Monte Karlo metode nastavljaju da budu jedne od najkorisnijih prisupa za naučna istraživanja zbog svoje jednostavnosti i opšte primenljivosti. Zbog konstantnog razvoja, sledeća generacija MK tehnika će obezbediti značajne alate za rešavanje sve složenijih problema procene očekivanja i optimizacije u različitim naučnim oblastima kao što su: finansije, statistika, matematika, biologija i dr.
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