AIMC Topic: Genes
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C-PUGP: A cluster-based positive unlabeled learning method for disease gene prediction and prioritization.
Computational biology and chemistry
Jun 1, 2018
Disease gene detection is an important stage in the understanding disease processes and treatment. Some candidate disease genes are identified using many machine learning methods Although there are some differences in these methods including feature ...
A statistical framework for biomedical literature mining.
Statistics in medicine
Jul 4, 2017
In systems biology, it is of great interest to identify new genes that were not previously reported to be associated with biological pathways related to various functions and diseases. Identification of these new pathway-modulating genes does not onl...
Character-level neural network for biomedical named entity recognition.
Journal of biomedical informatics
May 11, 2017
Biomedical named entity recognition (BNER), which extracts important named entities such as genes and proteins, is a challenging task in automated systems that mine knowledge in biomedical texts. The previous state-of-the-art systems required large a...
Machine learning identifies a compact gene set for monitoring the circadian clock in human blood.
Genome medicine
Feb 28, 2017
BACKGROUND: The circadian clock and the daily rhythms it produces are crucial for human health, but are often disrupted by the modern environment. At the same time, circadian rhythms may influence the efficacy and toxicity of therapeutics and the met...
Inferring Unknown Biological Function by Integration of GO Annotations and Gene Expression Data.
IEEE/ACM transactions on computational biology and bioinformatics
Oct 7, 2016
Characterizing genes with semantic information is an important process regarding the description of gene products. In spite that complete genomes of many organisms have been already sequenced, the biological functions of all of their genes are still ...
Annotating the Function of the Human Genome with Gene Ontology and Disease Ontology.
BioMed research international
Aug 22, 2016
Increasing evidences indicated that function annotation of human genome in molecular level and phenotype level is very important for systematic analysis of genes. In this study, we presented a framework named Gene2Function to annotate Gene Reference ...
The Markyt visualisation, prediction and benchmark platform for chemical and gene entity recognition at BioCreative/CHEMDNER challenge.
Database : the journal of biological databases and curation
Aug 19, 2016
Biomedical text mining methods and technologies have improved significantly in the last decade. Considerable efforts have been invested in understanding the main challenges of biomedical literature retrieval and extraction and proposing solutions to ...
Prediction and Validation of Disease Genes Using HeteSim Scores.
IEEE/ACM transactions on computational biology and bioinformatics
Feb 12, 2016
Deciphering the gene disease association is an important goal in biomedical research. In this paper, we use a novel relevance measure, called HeteSim, to prioritize candidate disease genes. Two methods based on heterogeneous networks constructed usin...
Lynx: a knowledge base and an analytical workbench for integrative medicine.
Nucleic acids research
Nov 20, 2015
Lynx (http://lynx.ci.uchicago.edu) is a web-based database and a knowledge extraction engine. It supports annotation and analysis of high-throughput experimental data and generation of weighted hypotheses regarding genes and molecular mechanisms cont...
A-DaGO-Fun: an adaptable Gene Ontology semantic similarity-based functional analysis tool.
Bioinformatics (Oxford, England)
Oct 17, 2015
SUMMARY: Gene Ontology (GO) semantic similarity measures are being used for biological knowledge discovery based on GO annotations by integrating biological information contained in the GO structure into data analyses. To empower users to quickly com...
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