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Items: 1 to 20 of 99

1.

Exploiting mid-range DNA patterns for sequence classification: binary abstraction Markov models.

Shepard SS, McSweeny A, Serpen G, Fedorov A.

Nucleic Acids Res. 2012 Jun;40(11):4765-73. doi: 10.1093/nar/gks154. Epub 2012 Feb 16.

2.

Determination of eukaryotic protein coding regions using neural networks and information theory.

Farber R, Lapedes A, Sirotkin K.

J Mol Biol. 1992 Jul 20;226(2):471-9.

PMID:
1640461
3.

Representation of DNA sequences in genetic codon context with applications in exon and intron prediction.

Yin C.

J Bioinform Comput Biol. 2015 Apr;13(2):1550004. doi: 10.1142/S0219720015500043. Epub 2014 Dec 10.

PMID:
25491390
4.

GeneGenerator--a flexible algorithm for gene prediction and its application to maize sequences.

Kleffe J, Hermann K, Vahrson W, Wittig B, Brendel V.

Bioinformatics. 1998;14(3):232-43.

PMID:
9614266
5.

Finding genes in DNA with a Hidden Markov Model.

Henderson J, Salzberg S, Fasman KH.

J Comput Biol. 1997 Summer;4(2):127-41.

PMID:
9228612
6.

Gene prediction with a hidden Markov model and a new intron submodel.

Stanke M, Waack S.

Bioinformatics. 2003 Oct;19 Suppl 2:ii215-25.

PMID:
14534192
7.

Detection of compositional constraints in nucleic acid sequences using neural networks.

Granjeon E, Tarroux P.

Comput Appl Biosci. 1995 Feb;11(1):29-37.

PMID:
7796272
8.

Classification of short human exons and introns based on statistical features.

Wu Y, Liew AW, Yan H, Yang M.

Phys Rev E Stat Nonlin Soft Matter Phys. 2003 Jun;67(6 Pt 1):061916. Epub 2003 Jun 27.

PMID:
16241270
9.

Coding exon detection using comparative sequences.

Wu J, Haussler D.

J Comput Biol. 2006 Jul-Aug;13(6):1148-64.

PMID:
16901234
10.

Parallel cascade recognition of exon and intron DNA sequences.

Korenberg MJ, Lipson ED, Green JR, Solomon JE.

Ann Biomed Eng. 2002 Jan;30(1):129-40.

PMID:
11874136
11.

Genome characterization through dichotomic classes: an analysis of the whole chromosome 1 of A. thaliana.

Properzi E, Giannerini S, Gonzalez DL, Rosa R.

Math Biosci Eng. 2013 Feb;10(1):199-219. doi: 10.3934/mbe.2013.10.199.

PMID:
23311369
12.

Vector space classification of DNA sequences.

Müller HM, Koonin SE.

J Theor Biol. 2003 Jul 21;223(2):161-9.

PMID:
12814599
14.
15.

In search of the small ones: improved prediction of short exons in vertebrates, plants, fungi and protists.

Saeys Y, Rouzé P, Van de Peer Y.

Bioinformatics. 2007 Feb 15;23(4):414-20. Epub 2007 Jan 4.

PMID:
17204465
16.

Analysing grouping of nucleotides in DNA sequences using lumped processes constructed from Markov chains.

Guédon Y, d'Aubenton-Carafa Y, Thermes C.

J Math Biol. 2006 Mar;52(3):343-72. Epub 2006 Feb 7.

PMID:
16463190
17.

Periodic sequence patterns in human exons.

Baldi P, Brunak S, Chauvin Y, Engelbrecht J, Krogh A.

Proc Int Conf Intell Syst Mol Biol. 1995;3:30-8.

PMID:
7584451
18.

Exons and introns characterization in nucleic acid sequences by time-frequency analysis.

Melia US, Claria F, Gallardo JJ, Caminal P, Perera A, Vallverdu M.

Conf Proc IEEE Eng Med Biol Soc. 2010;2010:1783-6. doi: 10.1109/IEMBS.2010.5626756.

PMID:
21096421
19.

Bacterial genomes lacking long-range correlations may not be modeled by low-order Markov chains: the role of mixing statistics and frame shift of neighboring genes.

Cocho G, Miramontes P, Mansilla R, Li W.

Comput Biol Chem. 2014 Dec;53 Pt A:15-25. doi: 10.1016/j.compbiolchem.2014.08.005. Epub 2014 Aug 30.

PMID:
25257406
20.

Eukaryotic gene prediction using GeneMark.hmm.

Borodovsky M, Lomsadze A, Ivanov N, Mills R.

Curr Protoc Bioinformatics. 2003 May;Chapter 4:Unit4.6. doi: 10.1002/0471250953.bi0406s01.

PMID:
18428701

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