subject: Molecular Biosciences date: 2013
10.4231/D3T727G0X
Catherine Rayon, Daisuke Kihara, Ishita K. Khan, Meghana Chitale
02/14/2013
The performances of PFP, ESG, and PSI-BLAST in predicting the functional diversity of moonlighting proteins were analyzed. PFP shows overall better performance in predicting diverse moonlighting functions as compared with PSI-BLAST and ESG. Recall by PSI-B...
Biochemistry Bioinformatics Molecular Biosciences proteomics
10.4231/D3Z02Z836
Daisuke Kihara, Meghana Chitale, Troy Hawkins
02/14/2013
BACKGROUND: A new paradigm of biological investigation takes advantage of technologies that produce large high throughput datasets, including genome sequences, interactions of proteins, and gene expression. The ability of biologists to analyze and interpre...
Biochemistry Bioinformatics Computational Biology / Methods Genetic Molecular Biosciences Proteins / Metabolism
10.4231/D3PK0719W
02/14/2013
Optimizing weighting factors for a linear combination of terms in a scoring function is a crucial step for success in developing a threading algorithm. Usually weighting factors are optimized to yield the highest success rate on a training dataset, and the...
Algorithms Biochemistry Bioinformatics databases Molecular Biosciences Protein Proteins / chemistry
10.4231/D3DR2P83H
Daisuke Kihara, H. Huang, Y.H. Tan
03/08/2013
Aligning distantly related protein sequences is a long-standing problem in bioinformatics, and a key for successful protein structure prediction. Its importance is increasing recently in the context of structural genomics projects because more and more exp...
Amino Acids/chemistry Biochemistry Bioinformatics Molecular Biosciences Protein Folding
10.4231/D37659F6Q
03/08/2013
In recent years, various families of small non-coding RNAs (sRNAs) have been discovered by experimental and computational approaches, both in bacterial and eukaryotic genomes. Although most of them await elucidation of their function, it has been reported...
Bacterial Bacterial/Genetics Biochemistry Bioinformatics Deinococcus/Genetics Escherichiacoli/Metabolism Molecular Biosciences Multigene Family RNA
10.4231/D3BZ61792
Bin Li, Daisuke Kihara, Manish Agrawal, Srinivasan Turuvekere
03/08/2013
Experimentally determined protein tertiary structures are rapidly accumulating in a database, partly due to the structural genomics projects. Included are proteins of unknown function, whose function has not been investigated by experiments and was not abl...
Argininosuccinate Synthase Binding Sites Biochemistry Bioinformatics Computer Simulation Molecular Biosciences Protein Structure Sensitivity and Specificity Tertiary Tetrahydrofolate Dehydrogenase/chemistry
10.4231/D33F4KN2K
Bin Li, Daisuke Kihara, Jianjun Hu
03/08/2013
Computational methods for de novo identification of gene regulation elements, such as transcription factor binding sites, have proved to be useful for deciphering genetic regulatory networks. However, despite the availability of a large number of algorithm...
Algorithms Base Sequence Binding Sites Biochemistry Bioinformatics Computational Biology / Methods DNA/Chemistry DNA/methods Escherichia coli/Genetics Factors/Metabolism Markov Chains Markov Chains Regulatory Sequences Molecular Biosciences Regulon Sequence Alignment Sequence Analysis
10.4231/D3DZ03214
Gregory E. Crawford, Minou Bina, Phillip J. Wyss, Sang P. Park, Sheryl A. Lazarus, Syed A. Shah, Wenhui Ren, Wojciech Szpankowski, Xiaohui C. Song
12/17/2013
In the human genome, regulatory signals are dispersed in DNA sequences and segments that control gene expression. We have developed a computational model to localize the position of potential regulatory signals in human genomic DNA. In this publication...
Binding-site Biochemistry Bioinformatics Codes in Human DNA DNASE-I hypersensitive sites Gene Regulation Genetic Vocabulary Human Genome Hypersensitive Sites Molecular Biosciences Promoter Regions Regulatory Signals Sequence Context Transcription factor binding sites Transcription Factors
10.4231/D31834278
Elwood A. Mullins, T. Joseph Kappock
10/22/2013
Vinegar production requires acetic acid bacteria that produce, tolerate, and conserve high levels of acetic acid. When ethanol is depleted, aerobic acetate “overoxidation” to carbon dioxide ensues. The resulting diauxic growth pattern has two logarithmic g...
Acidophile Biochemistry Chemistry citric acid cycle enzyme Molecular Biosciences
10.4231/D3WH2DF2W
Elwood A. Mullins, T. Joseph Kappock
10/22/2013
Vinegar production requires acetic acid bacteria that produce, tolerate, and conserve high levels of acetic acid. When ethanol is depleted, aerobic acetate “overoxidation” to carbon dioxide ensues. The resulting diauxic growth pattern has two logarithmic g...
Acidophile Biochemistry Chemistry citric acid cycle enzyme Molecular Biosciences
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