Topics
All (200)
alternative splicing (2)
Bayesian Networks (3)
clustering (3)
combinatorial optimization (1)
comparative genomics (8)
database construction (4)
database searching (1)
determining or using metabolic pathways and networks (3)
determining or using regulatory pathways and networks (3)
DNA sequencing (1)
drug design (1)
experiment design (1)
gene expression analysis (13)
gene networks (7)
gene prediction (3)
genome alignment/comparisons (1)
genome annotation (3)
genome evolution (3)
genome rearrangements (2)
haplotype modeling, finding, analysis (5)
haplotype use (2)
machine learning (7)
mass-spec technologies (4)
microarray design and/or data analysis (10)
models of evolution (6)
molecular evolution (2)
molecular modeling and/or docking (3)
multiple sequence alignment (3)
new technologies (1)
Other (7)
pairwise sequence alignment (2)
pattern and motif discovery (3)
phylogenetic analysis (3)
phylogenetics: algorithms (2)
protein function prediction (17)
protein interaction (8)
protein structure comparison (10)
protein structure prediction (9)
quantitative or population genetics (3)
regulatory region prediction (5)
RNA structure comparison (2)
RNA structure prediction (3)
sequence assembly (4)
SNP discovery or use (5)
splice site recognition (2)
statistics of motifs or strings (2)
string algorithms (1)
systems biology (6)
| - Ferre Fabrizio (Boston College) Diresidue neural network for the prediction of disulfide connectivity and ligand-bound cysteines
- Lu, Long (Yale University) The Limit of Genomic Data Integration for Predicting Protein-Protein Interactions: An Assessment using NaÔve Bayes Classifier
- Mukherjee, Sach (University of Oxford) Data-adaptive test statistics for microarray data
- Peters, Bjoern (La Jolla Institute for Allergy and Immunology) A Framework for Automating the Generation and Evaluation of Tools Predicting Peptide Binding to MHC class I Molecules
- Sebastian, Sethu (University of Massachussetts, Lowell) Using Machine Learning To Improve Gene Finding
- Spiridonov Alexey (NCBI, NLM, NIH) Applying machine learning for rational siRNA design
- Strope, Pooja (University of Nebraska - Lincoln) Comparative Analysis of Alignment-based and Alignment-free Protein Classifiers
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