Informace jsou predbezne.

Prednasejici: Dr. Matej Lexa, FI C506.
Konzultacni hodiny: Ct 13:00 - 15:00, nebo dle domluvy
Podzim 2010. Bude se schazet 1 h tydne (Ut 17:00-17:50 B411).
Diskusni forum

Predmet v oblasti aplikovane informatiky, ktery si klade za cil otevrit studentum dvere do fascinujiciho sveta molekul, genu a proteinu. Spolecnym tematem seminare pro podzim je "Predpovidani funkce a struktury proteinu ze sekvence".

Oficialni popis kurzu: IV105 (IS MU)

TYDEN
2-10) SEMINAR (studenti 20-30min/prezentaci)
(kazdy student si vybere jeden clanek k prezentaci na seminari)

Tema na seminar: http://www.lifl.fr/~noe/spaced_seeds.html

ODBORNE CLANKY


1)Programy pre R: Bioconductor (pripadne biopython alebo biojava)

2)Cao_et_al_2008.pdf ChemmineR: a compund mining framework for R

3)Li_et_al_2008.pdf Designing succint structural alphabets

4)PCpheno.pdf PCpheno R vignette

5)Miller_Eisenberg_2008.pdf Using inferred residue contacts to distinguish between correct and incorrect protein models

6)Newberg_2008.pdf Memory-efficient dynamic programming backtrace and pairwise local sequence alignment

Casopisy:
Bioinformatics, BMC Bioinformatics, Genome Biology, Proteins: structure, function, and bioinformatics

Predicting protein functions with message passing algorithms
M.Leone and A.Pagnani (2004). Bioinformatics (advance access, Sept 17) -RX-xerox

Protein beta-turn prediction using nearest-neighbor method
S.Kim (2004). Bioinformatics 20(1),40-44 -RX-xerox

MeKE: discovering the functions of gene products from biomedical literature via sentence alignment
J.-H. Chiang and H.-C.Yu (2003). Bioinformatics 19(11),1417-1422 -RX-xerox

Sensitive pattern discovery with 'fuzzy' alignments of distantly related proteins
A.Heger and L.Holm (2003). Bioinformatics 19(Suppl.1),130-137 -RX-xerox

Prediction of protein subcellular locations using fuzzy k-NN method
Y.Huang and Y.Li (2004). Bioinformatics 20(1),21-28 -RX-xerox

A novel method of protein secondary structure prediction with high segment overlap measure: support vector machine approach
S.Hua and Z.Sun (2001). JMB 308,397-407 -RX-xerox

Finding nuclear localization signals
M.Cokol et al. (2000). EMBO Reports 1(5),411-415 -RX-xerox

T16: Protein structure prediction using Rosetta
C.A.Rohl et al. (2004). Numerical Computer Methods, 66-93 -RX-xerox 

36) RECOMB 2001 -RX-K384.01-
37) RECOMB 2002 -RX-K384.02-
38) RECOMB 2003 -RX-K384.03-
39) RECOMB 2004 -RX-K384.04-
41) R.Nair, B.Rost 2004. Annotating protein function through lexical analysis, AI Mag., Spring 2004, 45-56. -RX-xerox-
42) R.D.King 2004. Applying Inductive logic programming to predicting gene function, AI Mag., Spring 2004, 57-68. -RX-xerox-
43a) LNCS 2149 O.Gascuel, B.M.E.Moret (Eds.) Algorithms in Bioinformatics, 2001 -K397.01
  N.von Ohsen, R.Zimmer. Improving profile-profile alignments via log average scoring, 11-26.
  J.Viksna,D.Gilbert. Pattern matching and pattern discovery algorithms for protein topologies. 98-111.
43b) LNCS XXXX R.Guigo,D.Gusfield (Eds.) Algorithms in Bioinformatics, 2002 -K397.02-
43c) LNCS XXXX G.Benson, R.Page (Eds.) Algorithms in Bioinformatics, 2003 -K397.03-
44) LNBI 2666 C.Guerra,S.Istrail (Eds.), Mathematical methods for protein structure analysis and design, 2003. 
  M.Kann, R.A.Goldstein. OPTIMA: A new score function for the detection of remote homologs, 99-108. 
  F.Seno et al. Learning effective amino-acid interactions, 139-145.
45) LNCS 2066 O.Gascuel, M.-F. Sagot (Eds.), Computational Biology, 2000
  N.Thierry-Mieg, L.Trilling. InterDB, a prediction-oriented protein interaction database for C.elegans., 135-146. -X-
46) LNCS 2388 S.-W. Lee, A.Verri (Eds.) Pattern recognition with support vector machines, 2002
  N.Mukherjee, S.Mukherjee. Predicting signal peptides with support vector machines, 1-7.

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