AIMC Topic: Computational Biology

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An Efficient Semi-supervised Learning Approach to Predict SH2 Domain Mediated Interactions.

Methods in molecular biology (Clifton, N.J.)
Src homology 2 (SH2) domain is an important subclass of modular protein domains that plays an indispensable role in several biological processes in eukaryotes. SH2 domains specifically bind to the phosphotyrosine residue of their binding peptides to ...

Exploring Genome-Wide Expression Profiles Using Machine Learning Techniques.

Methods in molecular biology (Clifton, N.J.)
Although contemporary high-throughput -omics methods produce high-dimensional data, the resulting wealth of information is difficult to assess using traditional statistical procedures. Machine learning methods facilitate the detection of additional p...

PREDICTIVE MODELING OF HOSPITAL READMISSION RATES USING ELECTRONIC MEDICAL RECORD-WIDE MACHINE LEARNING: A CASE-STUDY USING MOUNT SINAI HEART FAILURE COHORT.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
Reduction of preventable hospital readmissions that result from chronic or acute conditions like stroke, heart failure, myocardial infarction and pneumonia remains a significant challenge for improving the outcomes and decreasing the cost of healthca...

DEEP MOTIF DASHBOARD: VISUALIZING AND UNDERSTANDING GENOMIC SEQUENCES USING DEEP NEURAL NETWORKS.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
Deep neural network (DNN) models have recently obtained state-of-the-art prediction accuracy for the transcription factor binding (TFBS) site classification task. However, it remains unclear how these approaches identify meaningful DNA sequence signa...

Complementary Sources of Protein Functional Information: The Far Side of GO.

Methods in molecular biology (Clifton, N.J.)
The GO captures many aspects of functional annotations, but there are other alternative complementary sources of protein function information. For example, enzyme functional annotations are described in a range of resources from the Enzyme Commission...

The Evidence and Conclusion Ontology (ECO): Supporting GO Annotations.

Methods in molecular biology (Clifton, N.J.)
The Evidence and Conclusion Ontology (ECO) is a community resource for describing the various types of evidence that are generated during the course of a scientific study and which are typically used to support assertions made by researchers. ECO des...

Annotation Extensions.

Methods in molecular biology (Clifton, N.J.)
The specificity of knowledge that Gene Ontology (GO) annotations currently can represent is still restricted by the legacy format of the GO annotation file, a format intentionally designed for simplicity to keep the barriers to entry low and thus enc...

Semantic Similarity in the Gene Ontology.

Methods in molecular biology (Clifton, N.J.)
Gene Ontology-based semantic similarity (SS) allows the comparison of GO terms or entities annotated with GO terms, by leveraging on the ontology structure and properties and on annotation corpora. In the last decade the number and diversity of SS me...

Get GO! Retrieving GO Data Using AmiGO, QuickGO, API, Files, and Tools.

Methods in molecular biology (Clifton, N.J.)
The Gene Ontology Consortium (GOC) produces a wealth of resources widely used throughout the scientific community. In this chapter, we discuss the different ways in which researchers can access the resources of the GOC. We here share details about th...

Community-Wide Evaluation of Computational Function Prediction.

Methods in molecular biology (Clifton, N.J.)
A biological experiment is the most reliable way of assigning function to a protein. However, in the era of high-throughput sequencing, scientists are unable to carry out experiments to determine the function of every single gene product. Therefore, ...