AIMC Topic: Genomics

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KnowEnG: a knowledge engine for genomics.

Journal of the American Medical Informatics Association : JAMIA
We describe here the vision, motivations, and research plans of the National Institutes of Health Center for Excellence in Big Data Computing at the University of Illinois, Urbana-Champaign. The Center is organized around the construction of "Knowled...

Machine learning approach for pooled DNA sample calibration.

BMC bioinformatics
BACKGROUND: Despite ongoing reduction in genotyping costs, genomic studies involving large numbers of species with low economic value (such as Black Tiger prawns) remain cost prohibitive. In this scenario DNA pooling is an attractive option to reduce...

Application of comparative biology in GO functional annotation: the mouse model.

Mammalian genome : official journal of the International Mammalian Genome Society
The Gene Ontology (GO) is an important component of modern biological knowledge representation with great utility for computational analysis of genomic and genetic data. The Gene Ontology Consortium (GOC) consists of a large team of contributors incl...

Impact of relationships between test and training animals and among training animals on reliability of genomic prediction.

Journal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie
One of the factors affecting the reliability of genomic prediction is the relationship among the animals of interest. This study investigated the reliability of genomic prediction in various scenarios with regard to the relationship between test and ...

Identification of genomic features in the classification of loss- and gain-of-function mutation.

BMC medical informatics and decision making
BACKGROUND: Alterations of a genome can lead to changes in protein functions. Through these genetic mutations, a protein can lose its native function (loss-of-function, LoF), or it can confer a new function (gain-of-function, GoF). However, when a mu...

Machine learning applications in genetics and genomics.

Nature reviews. Genetics
The field of machine learning, which aims to develop computer algorithms that improve with experience, holds promise to enable computers to assist humans in the analysis of large, complex data sets. Here, we provide an overview of machine learning ap...

Woods: A fast and accurate functional annotator and classifier of genomic and metagenomic sequences.

Genomics
Functional annotation of the gigantic metagenomic data is one of the major time-consuming and computationally demanding tasks, which is currently a bottleneck for the efficient analysis. The commonly used homology-based methods to functionally annota...