AI Medical Compendium Journal:
Bioinformatics (Oxford, England)

Showing 31 to 40 of 847 articles

LncRNA-ID: Long non-coding RNA IDentification using balanced random forests.

Bioinformatics (Oxford, England)
MOTIVATION: Long non-coding RNAs (lncRNAs), which are non-coding RNAs of length above 200 nucleotides, play important biological functions such as gene expression regulation. To fully reveal the functions of lncRNAs, a fundamental step is to annotate...

Protein contact prediction by integrating joint evolutionary coupling analysis and supervised learning.

Bioinformatics (Oxford, England)
MOTIVATION: Protein contact prediction is important for protein structure and functional study. Both evolutionary coupling (EC) analysis and supervised machine learning methods have been developed, making use of different information sources. However...

OVA: integrating molecular and physical phenotype data from multiple biomedical domain ontologies with variant filtering for enhanced variant prioritization.

Bioinformatics (Oxford, England)
MOTIVATION: Exome sequencing has become a de facto standard method for Mendelian disease gene discovery in recent years, yet identifying disease-causing mutations among thousands of candidate variants remains a non-trivial task.

LoopIng: a template-based tool for predicting the structure of protein loops.

Bioinformatics (Oxford, England)
MOTIVATION: Predicting the structure of protein loops is very challenging, mainly because they are not necessarily subject to strong evolutionary pressure. This implies that, unlike the rest of the protein, standard homology modeling techniques are n...

A mutation profile for top-k patient search exploiting Gene-Ontology and orthogonal non-negative matrix factorization.

Bioinformatics (Oxford, England)
MOTIVATION: As the quantity of genomic mutation data increases, the likelihood of finding patients with similar genomic profiles, for various disease inferences, increases. However, so does the difficulty in identifying them. Similarity search based ...

High-order neural networks and kernel methods for peptide-MHC binding prediction.

Bioinformatics (Oxford, England)
MOTIVATION: Effective computational methods for peptide-protein binding prediction can greatly help clinical peptide vaccine search and design. However, previous computational methods fail to capture key nonlinear high-order dependencies between diff...

TPpred3 detects and discriminates mitochondrial and chloroplastic targeting peptides in eukaryotic proteins.

Bioinformatics (Oxford, England)
MOTIVATION: Molecular recognition of N-terminal targeting peptides is the most common mechanism controlling the import of nuclear-encoded proteins into mitochondria and chloroplasts. When experimental information is lacking, computational methods can...

TENET: topological feature-based target characterization in signalling networks.

Bioinformatics (Oxford, England)
MOTIVATION: Target characterization for a biochemical network is a heuristic evaluation process that produces a characterization model that may aid in predicting the suitability of each molecule for drug targeting. These approaches are typically used...

TRAL: tandem repeat annotation library.

Bioinformatics (Oxford, England)
MOTIVATION: Currently, more than 40 sequence tandem repeat detectors are published, providing heterogeneous, partly complementary, partly conflicting results.

PsyGeNET: a knowledge platform on psychiatric disorders and their genes.

Bioinformatics (Oxford, England)
UNLABELLED: PsyGeNET (Psychiatric disorders and Genes association NETwork) is a knowledge platform for the exploratory analysis of psychiatric diseases and their associated genes. PsyGeNET is composed of a database and a web interface supporting data...