AI Medical Compendium Journal:
Bioinformatics (Oxford, England)

Showing 41 to 50 of 847 articles

The SwissLipids knowledgebase for lipid biology.

Bioinformatics (Oxford, England)
MOTIVATION: Lipids are a large and diverse group of biological molecules with roles in membrane formation, energy storage and signaling. Cellular lipidomes may contain tens of thousands of structures, a staggering degree of complexity whose significa...

Identification of a small set of plasma signalling proteins using neural network for prediction of Alzheimer's disease.

Bioinformatics (Oxford, England)
MOTIVATION: Alzheimer's disease (AD) is a dementia that gets worse with time resulting in loss of memory and cognitive functions. The life expectancy of AD patients following diagnosis is ∼7 years. In 2006, researchers estimated that 0.40% of the wor...

KeBABS: an R package for kernel-based analysis of biological sequences.

Bioinformatics (Oxford, England)
KeBABS provides a powerful, flexible and easy to use framework for KE: rnel- B: ased A: nalysis of B: iological S: equences in R. It includes efficient implementations of the most important sequence kernels, also including variants that allow for tak...

ENVIRONMENTS and EOL: identification of Environment Ontology terms in text and the annotation of the Encyclopedia of Life.

Bioinformatics (Oxford, England)
UNLABELLED: The association of organisms to their environments is a key issue in exploring biodiversity patterns. This knowledge has traditionally been scattered, but textual descriptions of taxa and their habitats are now being consolidated in centr...

More challenges for machine-learning protein interactions.

Bioinformatics (Oxford, England)
MOTIVATION: Machine learning may be the most popular computational tool in molecular biology. Providing sustained performance estimates is challenging. The standard cross-validation protocols usually fail in biology. Park and Marcotte found that even...

GlycoMine: a machine learning-based approach for predicting N-, C- and O-linked glycosylation in the human proteome.

Bioinformatics (Oxford, England)
MOTIVATION: Glycosylation is a ubiquitous type of protein post-translational modification (PTM) in eukaryotic cells, which plays vital roles in various biological processes (BPs) such as cellular communication, ligand recognition and subcellular reco...

repDNA: a Python package to generate various modes of feature vectors for DNA sequences by incorporating user-defined physicochemical properties and sequence-order effects.

Bioinformatics (Oxford, England)
UNLABELLED: In order to develop powerful computational predictors for identifying the biological features or attributes of DNAs, one of the most challenging problems is to find a suitable approach to effectively represent the DNA sequences. To facili...

flowCL: ontology-based cell population labelling in flow cytometry.

Bioinformatics (Oxford, England)
MOTIVATION: Finding one or more cell populations of interest, such as those correlating to a specific disease, is critical when analysing flow cytometry data. However, labelling of cell populations is not well defined, making it difficult to integrat...

HyDRA: gene prioritization via hybrid distance-score rank aggregation.

Bioinformatics (Oxford, England)
UNLABELLED: Gene prioritization refers to a family of computational techniques for inferring disease genes through a set of training genes and carefully chosen similarity criteria. Test genes are scored based on their average similarity to the traini...

Automated structural classification of lipids by machine learning.

Bioinformatics (Oxford, England)
MOTIVATION: Modern lipidomics is largely dependent upon structural ontologies because of the great diversity exhibited in the lipidome, but no automated lipid classification exists to facilitate this partitioning. The size of the putative lipidome fa...