Posts Tagged ‘ GO ’

clusterProfiler in Bioconductor 2.8

March 26, 2011
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In recently years, high-throughput experimental techniques such as microarray and mass spectrometry can identify many lists of genes and gene products. The most widely used strategy for high-throughput data analysis is to identify different gene clusters based on their expression profiles. Another commonly used approach is to annotate these genes to biological knowledge, such as Gene Ontology (GO) and...

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The avalanche of publications mentioning GO

November 30, 2010
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The avalanche of publications mentioning GO

Gene Ontology is the de facto standard for annotation of gene products. It has been widely used in biological data mining, and I believe it will play more central role in the future.Publications mentioning GO was collected and deposited in GO ftp, and can be accessed (ftp://ftp.geneontology.org/go/doc/).Read More: 454 Words Totally

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The avalanche of publications mentioning GO

November 30, 2010
By
The avalanche of publications mentioning GO

Gene Ontology is the de facto standard for annotation of gene products. It has been widely used in biological data mining, and I believe it will play more central role in the future.Publications mentioning GO was collected and deposited in GO ftp, and can be accessed (ftp://ftp.geneontology.org/go/doc/).Read More: 454 Words Totally

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GOSemSim redesign in terms of S4 classes

November 30, 2010
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I started to develop GOSemSim package two years ago when I was not quite familiar with R. I am very happy to see that someone use it and found it helpful.I try to learn S4 and redesign GOSemSim with S4 classes and methods in the pass two weeks, and the very first version was implemented. As I’m not...

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Listing gene IDs from hyperGTest

October 19, 2010
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hyperGTest compute Hypergeomtric p-values for over or under-representation of each GO term in the specified category among the specified gene set.*geneSample* was used as an example.Read More: 1329 Words Totally

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Listing gene IDs from hyperGTest

October 19, 2010
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hyperGTest compute Hypergeomtric p-values for over or under-representation of each GO term in the specified category among the specified gene set.*geneSample* was used as an example.Read More: 1329 Words Totally

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ClusterProfiles

October 12, 2010
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ClusterProfiles

It is very common to cluster genes based on their expression profiles, and also very common to integrate Gene Ontology to observe the distribution of biological processes, molecular functions and cellular components for a given gene list. But, what if the two in combination? The Gene Ontology distributions across a variety of gene clusters may give us a new...

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ClusterProfiles

October 12, 2010
By
ClusterProfiles

It is very common to cluster genes based on their expression profiles, and also very common to integrate Gene Ontology to observe the distribution of biological processes, molecular functions and cellular components for a given gene list. But, what if the two in combination? The Gene Ontology distributions across a variety of gene clusters may give us a...

Read more »