<![CDATA[BOL: Related items]]> https://bioinformaticsonline.com/related/43376?offset=430 https://bioinformaticsonline.com/file/view/37581/comparativegenomics-exercise2 Wed, 22 Aug 2018 22:10:56 -0500 https://bioinformaticsonline.com/file/view/37581/comparativegenomics-exercise2 <![CDATA[ComparativeGenomics Exercise2]]> COMPARATIVE MICROBIAL GENOMICS ANALYSIS WORKSHOP  @ cbs.dtu.dk

Free Bioinformatics workbench https://www.mn.uio.no/ifi/english/research/networks/clsi/earlier_seminars/2012/tammivesth_osloseminarfinal.pdf

]]> Neel https://bioinformaticsonline.com/bookmarks/view/38039/vgsc-a-web-based-vector-graph-toolkit-of-genome-synteny-and-collinearity Tue, 30 Oct 2018 10:46:28 -0500 https://bioinformaticsonline.com/bookmarks/view/38039/vgsc-a-web-based-vector-graph-toolkit-of-genome-synteny-and-collinearity <![CDATA[VGSC: A Web-Based Vector Graph Toolkit of Genome Synteny and Collinearity]]> VGSC, the Vector Graph toolkit of genome Synteny and Collinearity, and its online service, to visualize the synteny and collinearity in the common graphical format, including both raster (JPEG, Bitmap, and PNG) and vector graphic (SVG, EPS, and PDF). 

Address of the bookmark: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4783527/

]]> Abhimanyu Singh https://bioinformaticsonline.com/researchlabs/view/38418/charles-swanton-lab Tue, 11 Dec 2018 08:09:22 -0600 <![CDATA[CHARLES SWANTON LAB]]> They are using the latest DNA sequencing technology to read the genetic makeup of cancer cells within tumours in ever greater detail, teasing out patterns of evolution (evolutionary rule books), cancer heterogeneity and working out what changes have happened as a tumour evolves. We’re also investigating the processes that cause mutations and accelerate tumour evolution and working out how they might be stopped. And we are running evolutionary clinical trials with immune and targeted therapies to bring the benefits of our work to patients as quickly as possible.

https://www.crick.ac.uk/research/labs/charles-swanton

]]> https://bioinformaticsonline.com/bookmarks/view/38735/genome-assembly-tutorial-genome-assembly-for-short-and-long-reads Sat, 19 Jan 2019 17:29:53 -0600 https://bioinformaticsonline.com/bookmarks/view/38735/genome-assembly-tutorial-genome-assembly-for-short-and-long-reads <![CDATA[Genome assembly tutorial "Genome Assembly for short and long reads"]]> In this lab we will perform de novo genome assembly of a bacterial genome. You will be guided through the genome assembly starting with data quality control, through to building contigs and analysis of the results. At the end of the lab you will know:

  1. How to perform basic quality checks on the input data
  2. How to run a short read assembler on Illumina data
  3. How to run a long read assembler on Pacific Biosciences or Oxford Nanopore data
  4. How to improve the accuracy of a long read assembly using short reads
  5. How to assess the quality of an assembly

https://bioinformaticsdotca.github.io/high-throughput_biology_2017

Address of the bookmark: https://bioinformaticsdotca.github.io/high-throughput_biology_2017_module6_lab

]]> Jit https://bioinformaticsonline.com/bookmarks/view/39250/darwin-wga-a-co-processor-provides-increased-sensitivity-in-whole-genome-alignments-with-high-speedup Sat, 13 Apr 2019 08:55:31 -0500 https://bioinformaticsonline.com/bookmarks/view/39250/darwin-wga-a-co-processor-provides-increased-sensitivity-in-whole-genome-alignments-with-high-speedup <![CDATA[Darwin-WGA: A Co-processor Provides Increased Sensitivity in Whole Genome Alignments with High Speedup]]> Darwin-WGA, is the first hardware accelerator for whole genome alignment and accelerates the gapped filtering stage. Darwin-WGA also employs GACT-X, a novel algorithm used in the extension stage to align arbitrarily long genome sequences using a small on-chip memory, that provides better quality alignments at 2× improvement in memory and speed over the previously published GACT algorithm. Implemented on an FPGA, Darwin-WGA provides up to 24× improvement (performance/$) in WGA over iso-sensitive software.

https://stanford.edu/~yatisht/pubs/darwin-wga.pdf

Address of the bookmark: https://github.com/gsneha26/Darwin-WGA

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