AIMC Topic: Computational Biology

Clear Filters Showing 3041 to 3050 of 4583 articles

A Graph Approach to Mining Biological Patterns in the Binding Interfaces.

Journal of computational biology : a journal of computational molecular cell biology
Protein-RNA interactions play important roles in the biological systems. Searching for regular patterns in the Protein-RNA binding interfaces is important for understanding how protein and RNA recognize each other and bind to form a complex. Herein, ...

Prediction of Protein-Protein Interactions by Evidence Combining Methods.

International journal of molecular sciences
Most cellular functions involve proteins' features based on their physical interactions with other partner proteins. Sketching a map of protein-protein interactions (PPIs) is therefore an important inception step towards understanding the basics of c...

Prediction of microRNAs involved in immune system diseases through network based features.

Journal of biomedical informatics
MicroRNAs are a class of small non-coding regulatory RNA molecules that modulate the expression of several genes at post-transcriptional level and play a vital role in disease pathogenesis. Recent research shows that a range of miRNAs are involved in...

State Estimation for Delayed Genetic Regulatory Networks With Reaction-Diffusion Terms.

IEEE transactions on neural networks and learning systems
This paper addresses the problem of state estimation for delayed genetic regulatory networks (DGRNs) with reaction-diffusion terms using Dirichlet boundary conditions. The nonlinear regulation function of DGRNs is assumed to exhibit the Hill form. Th...

SNooPer: a machine learning-based method for somatic variant identification from low-pass next-generation sequencing.

BMC genomics
BACKGROUND: Next-generation sequencing (NGS) allows unbiased, in-depth interrogation of cancer genomes. Many somatic variant callers have been developed yet accurate ascertainment of somatic variants remains a considerable challenge as evidenced by t...

Advanced literature analysis in a Big Data world.

Annals of the New York Academy of Sciences
Comprehensive data mining of the scientific literature has become an increasing challenge. To address this challenge, Elsevier's Pathway Studio software uses the techniques of natural language processing to systematically extract specific biological ...

Inferring Weighted Directed Association Network from Multivariate Time Series with a Synthetic Method of Partial Symbolic Transfer Entropy Spectrum and Granger Causality.

PloS one
Complex network methodology is very useful for complex system explorer. However, the relationships among variables in complex system are usually not clear. Therefore, inferring association networks among variables from their observed data has been a ...

SGFSC: speeding the gene functional similarity calculation based on hash tables.

BMC bioinformatics
BACKGROUND: In recent years, many measures of gene functional similarity have been proposed and widely used in all kinds of essential research. These methods are mainly divided into two categories: pairwise approaches and group-wise approaches. Howev...

Fuzzy-Rough Entropy Measure and Histogram Based Patient Selection for miRNA Ranking in Cancer.

IEEE/ACM transactions on computational biology and bioinformatics
MicroRNAs (miRNAs) are known as an important indicator of cancers. The presence of cancer can be detected by identifying the responsible miRNAs. A fuzzy-rough entropy measure (FREM) is developed which can rank the miRNAs and thereby identify the rele...

A New Data Representation Based on Training Data Characteristics to Extract Drug Name Entity in Medical Text.

Computational intelligence and neuroscience
One essential task in information extraction from the medical corpus is drug name recognition. Compared with text sources come from other domains, the medical text mining poses more challenges, for example, more unstructured text, the fast growing of...