BOL: Related items

NanoSim: nanopore sequence read simulator based on statistical characterization.

Jit — Mon, 18 Dec 2017 04:16:31 -0600

NanoSim, a fast and scalable read simulator that captures the technology-specific features of ONT data and allows for adjustments upon improvement of nanopore sequencing technology. The first step of NanoSim is read characterization, which provides a comprehensive alignment-based analysis and generates a set of read profiles serving as the input to the next step, the simulation stage. The simulation stage uses the model built in the previous step to produce in silico reads for a given reference genome. NanoSim is written in Python and R. The source files and manual are available at the Genome Sciences Centre website: http://www.bcgsc.ca/platform/bioinfo/software/nanosim

https://github.com/bcgsc/NanoSim

Address of the bookmark: http://www.bcgsc.ca/platform/bioinfo/software/nanosim

Interview Mark Sansom (U. Oxford): Simulations of Membrane Proteins

Mon, 07 Oct 2013 14:34:13 -0500

Workshop in Bioinformatics, 4/June/2012 Campus Vida's Research Centers organize in Santiago de Compostela the Workshop in Bioinformatics. This event addressed issues such as structural bioinformatics, biological modelling and mining bioinformatics data. Professor Mark Sansom (University of Oxford), belonging to the Structural Bioinformatics and Computational Biochemistr Unit, opened the sessions with the lecture "Multiscale Simulations of Membrane Proteins: Lipid Interactions and Signalling".

orthodotter: Synteny plots (oxford grid)

Jit — Wed, 09 Aug 2017 07:16:16 -0500

orthodotter -h
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orthodotter - Plot orthologous genes on an oxford grid.
       -f      : input file, containing orthologous genes, default is stdin
                       species chr-name start end species chr-name start end
       -toPlot  : give the x and y sets and the color separated by double-dots,
                       for example set1:set2:red will plot set1 on x, set2 on y with
                       red points. Could give several -toPlot arguments.
                       To launch the clustering of dots, use extra-option 1=dist,min_nb_genes
                       where dist is the minimal distance (euclidian) between two points and min_nb_genes the minimal
                       number of genes in a cluster to be valid.
       -o      : output file, default is stdout
       -x       : resolution of x axis, default is 600
       -y       : resolution on y axis, default is 600
       -r       : radius of circle representing orthologous genes
       -format       : could be png, gif, jpg, pdf or ps. Default is png.
       -fg           : foreground color, default is black
       -bg           : background color, default is transparent
       -fSize   : fontSize, default is 1
       -filter       : check chromosome names
       -h            : help
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orthodotter -f Vigne_Banane.ortho -toPlot Vigne:Banane:black:1=10,5 -x 1200 -y 1200 -bg white -o Vigne_vs_Banane.png > Vigne_vs_Banane.clusters
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Address of the bookmark: https://github.com/institut-de-genomique/orthodotter

Should you get sequenced? Not all bad genes predict disease

Rahul Agarwal — Thu, 29 Aug 2013 15:10:53 -0500

“What we really don’t know yet is whether the predictive aspects of the genome are going to turn out to be beneficial or potentially harmful”

“As we roll out genomic medicine we are fighting against this society-wide misconception that having the bad gene means you’re going to get the disease. That’s only true in a very few cases.”

Source:Today Health

Address of the bookmark: http://www.today.com/health/should-you-get-sequenced-not-all-bad-genes-predict-disease-8C11017154

Two major breakthrough!!

Rahul Agarwal — Mon, 02 Sep 2013 10:18:11 -0500

"Scientists in Uruguay in colloboration with European partners sequenced the genome of the high-value Tannat grape, from which "the most healthy of red wines" are fermented.

A quick, $1 syphilis test in development by researchers from UNU-BIOLAC."

Source:

http://www.sciencedaily.com/releases/2013/09/130902101846.htm

http://www.eurekalert.org/pub_releases/2013-09/tca-ssg082613.php

Encode sequencing data freely available to download and use for academic means

Rahul Agarwal — Thu, 13 Mar 2014 18:18:08 -0500

In Encode, regulatory elements investigated via DNA hypersensitivity assays, assays of DNA methylation, and chromatin immunoprecipitation (ChIP) of proteins that interact with DNA, including modified histones and transcription factors, followed by sequencing (ChIP-Seq).

More information:

https://genome.ucsc.edu/ENCODE/pilot.html

Address of the bookmark: https://genome.ucsc.edu/ENCODE/

Tsetse Fly Genome sequenced

Rahul Agarwal — Fri, 25 Apr 2014 10:48:35 -0500

As it reported online today in Science, the team used several sequencing approaches to tackle the tsetse fly's 366 million base genome.

The current study, and companion articles slated to appear in PLOS One, PLOS Genetics, and PLOS Neglected Tropic Diseases, are the result of nearly 150 researchers based in 18 countries.

Source:

http://www.genomeweb.com/sequencing/international-team-sequences-tsetse-fly-genome

Science for Life Laboratory (SciLifeLab)-Sweden

Sat, 10 May 2014 06:22:30 -0500

Science for Life Laboratory (SciLifeLab) is a national center for molecular biosciences with focus on health and environmental research. The center combines frontline technical expertise with advanced knowledge of translational medicine and molecular bioscience. SciLifeLab is a national resource and a collaboration between four universities: Karolinska Institutet, KTH Royal Institute of Technology, Stockholm University and Uppsala University.

Webpage : https://www.scilifelab.se/about-us/
Opportunity: https://www.scilifelab.se/about-us/career/

Genomics and sequencing approach for identification of biomarkers to assess the efficacy of TGF-βRI inhibitors (of liver cancer) in vivo

Rahul Agarwal — Tue, 05 Aug 2014 13:55:32 -0500

Liver cancer is third leading cause of deaths and fourth most frequent occuring cancer worldwide. There are multiple signaling pathways responsible for causing cancer amongst which TGFb is most important cytokine whose signaling pathway promote cancer. However, main problem is to cure this cancer at late stage where we still have no treatment strategy to tackle this deadly cancer. Hence we need to find out new therapeutic target. One way is to look the relationships between mRNA, methylation and miRNA data of patients with different pathological conditions (cancer vs control either with inhibitor/not). MiRNA is small RNA molecules known to inhibit mRNA expression of particular gene by binding improperly to 3'UTR region of a gene and hence block binding of TF /translation of gene. CpG regions is known to located at promoter region of gene (5' UTR) and usually hypomethylated which allow to gene to transcribe and translate however sometime this region become hyper-methylated thats prevent expression of host gene. Thus , integration of these three data reveal new targets and pathways important for causing or preventing cancer and also reveal biomarker thats check the effects of inhibitor on signaling pathway underlying liver cancer.

CovCal: Coverage / Read Count Calculator

Jit — Wed, 15 Jun 2016 18:08:13 -0500

Coverage / Read Count Calculator

Calculate how much sequencing you need to hit a target depth of coverage (or vice versa).

Instructions: set the read length/configuration and genome size, then select what you want to calculate.

Written by Stephen Turner, based on the Lander-Waterman formula, inspired by a similar calculator written by James Hadfield. Coverage is calculated as C=LN/G and reads as N=CG/L where C = Coverage (X),L = Read length (bp), G = Haploid genome size (bp), and N = Number of reads. Source code on GitHub.

Address of the bookmark: http://apps.bioconnector.virginia.edu/covcalc/