Computational Lab - Prof. Cristian Coarfa (2009)

submitted by: ralanharris

An introduction to computational methods for analyzing ChIP-Seq data by Cristian Coarfa. This was presented as a lab within the Computer Aided Discovery Methods course offered within the Graduate Program at Baylor College of Medicine.

Challenges in Ecological Metagenomics

submitted by: dougramsey
Since the first metagenomics study was published 17 years ago, the ability to make ecological inferences has been limited by sequencing throughput and the ability to analyze the data. Yet, if the potential of metagenomics to help us decipher the structure and function of microbial ecosystems is to be realized, it is essential that our bioinformatics tools motivate our sequencing efforts. This is analogous to the bioinformatics advances that were made to accelerating the sequencing of the...

TimeLogic

submitted by: dougramsey
Delivering the performance equivalent of hundreds to over one thousand CPU cores per accelerated node, the TimeLogic solutions are ideal for data-intensive next-generation genomics. Life science institutions worldwide have chosen the TimeLogic brand as their optimal solution for high-throughput bioinformatics. The DeCypher and CodeQuest biocomputing solutions blend proven bioinformatics algorithms with ultra-fast accelerator hardware to achieve a perfect combination of performance, accuracy,...

Integrated Information System for Genomic and Metagenomic Data Analysis at National Center for Biotechnology Information (NCBI)

submitted by: dougramsey
Recent advances in biotechnology and bioinformatics has provided a flood of genomic data and tremendous growth in the number of associated data sets. Sequencing projects now include draft assemblies, complete genomes, comparative genomics, and metagenomics where genetic material is sequenced directly from environmental samples. The NCBI provides integrated systems for data storage, retrieval, and analysis. GenBank, an archival database of DNA sequences, contains consensus sequences assembled...

Gene Expression Computational Lab - Chris Miller

submitted by: ralanharris

An introduction to computational methods for analyzing gene expression data by Chris Miller. This was presented as a lab within the Computer Aided Discovery Methods course offered within the Graduate Program at Baylor College of Medicine.

Transcriptional Regulatory Pathways - Prof. Chad Creighton (Part 2, 2009)

submitted by: ralanharris

Prof. Chad Creighton lectures on examining ranscriptional regulatory pathways in cancer using microarrays. Part of the Computer Aided Discovery Methods 2009 course offered at Baylor College of Medicine.

Transcriptional Regulatory Pathways - Prof. Chad Creighton (Part 1, 2009)

submitted by: ralanharris

Prof. Chad Creighton lectures on examining ranscriptional regulatory pathways in cancer using microarrays. Part of the Computer Aided Discovery Methods 2009 course offered at Baylor College of Medicine.

Studies of Genome Variation - Prof. Aleks Milosavljevic (Part 2, 2009)

submitted by: ralanharris

Prof. Aleks Milosavljevic lectures on insights into cancer biology from resequencing of cancer genomes and from mapping of chromosomal rearrangements in cancer using array CGH and end-sequence profiling. Part of the Computer Aided Discovery Methods 2009 course offered at Baylor College of Medicine.

Studies of Genome Variation - Prof. Aleks Milosavljevic (Part 1, 2009)

submitted by: ralanharris

Prof. Aleks Milosavljevic lectures on insights into cancer biology from resequencing of cancer genomes and from mapping of chromosomal rearrangements in cancer using array CGH and end-sequence profiling. Part of the Computer Aided Discovery Methods 2009 course offered at Baylor College of Medicine.

Ruby and the Genboree API - Andrew Jackson

submitted by: ralanharris

An introduction to Ruby and it use in the Genboree genomics tool (www.genboree.org) API. This was presented as part of the "Data Integration Using Ruby" lab of the Computer Aided Discovery Methods course offered within the Graduate Program at Baylor College of Medicine.