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Computational methods
Computational Methods include useful new routines and algorithms with applications to Bioinformatics such as new sequence manipulation and analysis methods. Also included are new methods of computational analysis of biological data that facilitate data interpretation.
Citations 221-230 of 359 total displayed.
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Transcribed processed pseudogenes in the human genome: an intermediate form of expressed retrosequence lacking protein-coding ability
- Paul M. Harrison, Deyou Zheng, Zhaolei Zhang, Nicholas Carriero, and Mark Gerstein
Nucleic Acids Res. 2005; 33: 2374-2383.
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TM-align: a protein structure alignment algorithm based on the TM-score
- Yang Zhang and Jeffrey Skolnick
Nucleic Acids Res. 2005; 33: 2302-2309.
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Computational technique for improvement of the position-weight matrices for the DNA/protein binding sites
- Naum I. Gershenzon, Gary D. Stormo, and Ilya P. Ioshikhes
Nucleic Acids Res. 2005; 33: 2290-2301.
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Detecting DNA-binding helix–turn–helix structural motifs using sequence and structure information
- Marialuisa Pellegrini-Calace and Janet M. Thornton
Nucleic Acids Res. 2005; 33: 2129-2140.
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Comparative gene finding in chicken indicates that we are closing in on the set of multi-exonic widely expressed human genes
- Robert Castelo, Alexandre Reymond, Carine Wyss, Francisco Câmara, Genís Parra, Stylianos E. Antonarakis, Roderic Guigó, and Eduardo Eyras
Nucleic Acids Res. 2005; 33: 1935-1939.
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A computational study of off-target effects of RNA interference
- Shibin Qiu, Coen M. Adema, and Terran Lane
Nucleic Acids Res. 2005; 33: 1834-1847.
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Sequence variation in G-protein-coupled receptors: analysis of single nucleotide polymorphisms
- Suganthi Balasubramanian, Yu Xia, Elizaveta Freinkman, and Mark Gerstein
Nucleic Acids Res. 2005; 33: 1710-1721.
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Integration of text- and data-mining using ontologies successfully selects disease gene candidates
- Nicki Tiffin, Janet F. Kelso, Alan R. Powell, Hong Pan, Vladimir B. Bajic, and Winston A. Hide
Nucleic Acids Res. 2005; 33: 1544-1552.
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NestedMICA: sensitive inference of over-represented motifs in nucleic acid sequence
- Thomas A. Down and Tim J. P. Hubbard
Nucleic Acids Res. 2005; 33: 1445-1453.
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Human pol II promoter prediction: time series descriptors and machine learning
- Rajeev Gangal and Pankaj Sharma
Nucleic Acids Res. 2005; 33: 1332-1336.
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