AIMC Topic: Databases, Protein

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An ontology for major histocompatibility restriction.

Journal of biomedical semantics
BACKGROUND: MHC molecules are a highly diverse family of proteins that play a key role in cellular immune recognition. Over time, different techniques and terminologies have been developed to identify the specific type(s) of MHC molecule involved in ...

Towards Extracting Supporting Information About Predicted Protein-Protein Interactions.

IEEE/ACM transactions on computational biology and bioinformatics
One of the goals of relation extraction is to identify protein-protein interactions (PPIs) in biomedical literature. Current systems are capturing binary relations and also the direction and type of an interaction. Besides assisting in the curation P...

Accurate refinement of docked protein complexes using evolutionary information and deep learning.

Journal of bioinformatics and computational biology
One of the major challenges for protein docking methods is to accurately discriminate native-like structures from false positives. Docking methods are often inaccurate and the results have to be refined and re-ranked to obtain native-like complexes a...

Prediction of Protein-Protein Interaction Sites with Machine-Learning-Based Data-Cleaning and Post-Filtering Procedures.

The Journal of membrane biology
Accurately predicting protein-protein interaction sites (PPIs) is currently a hot topic because it has been demonstrated to be very useful for understanding disease mechanisms and designing drugs. Machine-learning-based computational approaches have ...

Continuous Distributed Representation of Biological Sequences for Deep Proteomics and Genomics.

PloS one
We introduce a new representation and feature extraction method for biological sequences. Named bio-vectors (BioVec) to refer to biological sequences in general with protein-vectors (ProtVec) for proteins (amino-acid sequences) and gene-vectors (Gene...

Prediction Enhancement of Residue Real-Value Relative Accessible Surface Area in Transmembrane Helical Proteins by Solving the Output Preference Problem of Machine Learning-Based Predictors.

Journal of chemical information and modeling
The α-helical transmembrane proteins constitute 25% of the entire human proteome space and are difficult targets in high-resolution wet-lab structural studies, calling for accurate computational predictors. We present a novel sequence-based method ca...

Survey of Natural Language Processing Techniques in Bioinformatics.

Computational and mathematical methods in medicine
Informatics methods, such as text mining and natural language processing, are always involved in bioinformatics research. In this study, we discuss text mining and natural language processing methods in bioinformatics from two perspectives. First, we...

Illuminating the dark matter in metabolomics.

Proceedings of the National Academy of Sciences of the United States of America

Prediction of recombinant protein overexpression in Escherichia coli using a machine learning based model (RPOLP).

Computers in biology and medicine
Recombinant protein overexpression, an important biotechnological process, is ruled by complex biological rules which are mostly unknown, is in need of an intelligent algorithm so as to avoid resource-intensive lab-based trial and error experiments i...

Accurate pan-specific prediction of peptide-MHC class II binding affinity with improved binding core identification.

Immunogenetics
A key event in the generation of a cellular response against malicious organisms through the endocytic pathway is binding of peptidic antigens by major histocompatibility complex class II (MHC class II) molecules. The bound peptide is then presented ...