AIMC Topic: Computational Biology

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BelSmile: a biomedical semantic role labeling approach for extracting biological expression language from text.

Database : the journal of biological databases and curation
Biological expression language (BEL) is one of the most popular languages to represent the causal and correlative relationships among biological events. Automatically extracting and representing biomedical events using BEL can help biologists quickly...

Generating Gene Ontology-Disease Inferences to Explore Mechanisms of Human Disease at the Comparative Toxicogenomics Database.

PloS one
Strategies for discovering common molecular events among disparate diseases hold promise for improving understanding of disease etiology and expanding treatment options. One technique is to leverage curated datasets found in the public domain. The Co...

Clustering Single-Cell Expression Data Using Random Forest Graphs.

IEEE journal of biomedical and health informatics
Complex tissues such as brain and bone marrow are made up of multiple cell types. As the study of biological tissue structure progresses, the role of cell-type-specific research becomes increasingly important. Novel sequencing technology such as sing...

OmniSearch: a semantic search system based on the Ontology for MIcroRNA Target (OMIT) for microRNA-target gene interaction data.

Journal of biomedical semantics
As a special class of non-coding RNAs (ncRNAs), microRNAs (miRNAs) perform important roles in numerous biological and pathological processes. The realization of miRNA functions depends largely on how miRNAs regulate specific target genes. It is there...

DiscMLA: An Efficient Discriminative Motif Learning Algorithm over High-Throughput Datasets.

IEEE/ACM transactions on computational biology and bioinformatics
The transcription factors (TFs) can activate or suppress gene expression by binding to specific sites, hence are crucial regulatory elements for transcription. Recently, series of discriminative motif finders have been tailored to offering promising ...

Pattern Classification of Instantaneous Cognitive Task-load Through GMM Clustering, Laplacian Eigenmap, and Ensemble SVMs.

IEEE/ACM transactions on computational biology and bioinformatics
The identification of the temporal variations in human operator cognitive task-load (CTL) is crucial for preventing possible accidents in human-machine collaborative systems. Recent literature has shown that the change of discrete CTL level during hu...

Enrichr: a comprehensive gene set enrichment analysis web server 2016 update.

Nucleic acids research
Enrichment analysis is a popular method for analyzing gene sets generated by genome-wide experiments. Here we present a significant update to one of the tools in this domain called Enrichr. Enrichr currently contains a large collection of diverse gen...

APPAGATO: an APproximate PArallel and stochastic GrAph querying TOol for biological networks.

Bioinformatics (Oxford, England)
MOTIVATION: Biological network querying is a problem requiring a considerable computational effort to be solved. Given a target and a query network, it aims to find occurrences of the query in the target by considering topological and node similariti...

The Ontology for Biomedical Investigations.

PloS one
The Ontology for Biomedical Investigations (OBI) is an ontology that provides terms with precisely defined meanings to describe all aspects of how investigations in the biological and medical domains are conducted. OBI re-uses ontologies that provide...

Deep Neural Networks as a Computational Model for Human Shape Sensitivity.

PLoS computational biology
Theories of object recognition agree that shape is of primordial importance, but there is no consensus about how shape might be represented, and so far attempts to implement a model of shape perception that would work with realistic stimuli have larg...