AIMC Topic: Computational Biology

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Improve Biomedical Information Retrieval Using Modified Learning to Rank Methods.

IEEE/ACM transactions on computational biology and bioinformatics
In these years, the number of biomedical articles has increased exponentially, which becomes a problem for biologists to capture all the needed information manually. Information retrieval technologies, as the core of search engines, can deal with the...

A machine-learning approach for predicting palmitoylation sites from integrated sequence-based features.

Journal of bioinformatics and computational biology
Palmitoylation is the covalent attachment of lipids to amino acid residues in proteins. As an important form of protein posttranslational modification, it increases the hydrophobicity of proteins, which contributes to the protein transportation, orga...

TaggerOne: joint named entity recognition and normalization with semi-Markov Models.

Bioinformatics (Oxford, England)
MOTIVATION: Text mining is increasingly used to manage the accelerating pace of the biomedical literature. Many text mining applications depend on accurate named entity recognition (NER) and normalization (grounding). While high performing machine le...

The Proteasix Ontology.

Journal of biomedical semantics
BACKGROUND: The Proteasix Ontology (PxO) is an ontology that supports the Proteasix tool; an open-source peptide-centric tool that can be used to predict automatically and in a large-scale fashion in silico the proteases involved in the generation of...

Integrative Analysis of Proteomic, Glycomic, and Metabolomic Data for Biomarker Discovery.

IEEE journal of biomedical and health informatics
Studies associating changes in the levels of multiple biomolecules including proteins, glycans, glycoproteins, and metabolites with the onset of cancer have been widely investigated to identify clinically relevant diagnostic biomarkers. Advances in l...

Toward High-Throughput Predictive Modeling of Protein Binding/Unbinding Kinetics.

Journal of chemical information and modeling
One of the unaddressed challenges in drug discovery is that drug potency determined in vitro is not a reliable indicator of drug activity in vivo. Accumulated evidence suggests that in vivo activity is more strongly correlated with the binding/unbind...

Effectively Identifying Compound-Protein Interactions by Learning from Positive and Unlabeled Examples.

IEEE/ACM transactions on computational biology and bioinformatics
Prediction of compound-protein interactions (CPIs) is to find new compound-protein pairs where a protein is targeted by at least a compound, which is a crucial step in new drug design. Currently, a number of machine learning based methods have been d...

BELTracker: evidence sentence retrieval for BEL statements.

Database : the journal of biological databases and curation
Biological expression language (BEL) is one of the main formal representation models of biological networks. The primary source of information for curating biological networks in BEL representation has been literature. It remains a challenge to ident...