BOL: Related items

Molecular Genetics Lecture

Rahul Agarwal — Fri, 27 Sep 2013 04:24:45 -0500

"Robert Sapolsky makes interdisciplinary connections between behavioral biology and molecular genetic influences. He relates protein synthesis and point mutations to microevolutionary change, and discusses conflicting theories of gradualism and punctuated equilibrium and the influence of epigenetics on development theories."

"Robert Sapolsky is an American neuroendocrinologist, professor of biology, neuroscience, and neurosurgery at Stanford University, researcher and author" ----Wikipedia

Address of the bookmark: http://www.youtube.com/watch?v=_dRXA1_e30o

Bioinformatics infrastructure speed up Indian agriculture

Rahul Agarwal — Tue, 07 Jan 2014 12:44:44 -0600

"Realizing the paradigm shift it can bring about, the government is focusing on increased bioinformatics intervention in agri-sciences. Currently under process, the national grid on bioinformatics is expected make much better sense out of huge genomic" -

http://www.biospectrumindia.com/biospecindia/features/203849/supercomputing-indian-agriculture-fast-track-mode/page/1

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/

Webinar on Streamlining large scale analysis using the Strand NGS Pipeline Manager on 24 Feb 2016

Yeshodari — Fri, 05 Feb 2016 06:43:28 -0600

Live Webinar on Streamlining large scale NGS data analysis using the Strand NGS Pipeline Manager on 24 Feb 2016

Abstract: Strand NGS includes comprehensive workflows for DNA-Seq, RNA-Seq, Small RNA-Seq, ChIP-Seq, MeDIP-Seq, and Methyl-Seq analysis. Each workflow includes a quality assessment and filter section, followed by a workflow-specific analysis section. The pipeline functionality in Strand NGS allows users to execute a sequence of analysis steps with specific parameters - all without any manual intervention. This simplifies the analysis in large scale sequencing projects where every sample needs to be processed identically.

In this webinar we will discuss the pre-packaged pipelines present in Strand NGS. The packaged pipelines have well-chosen default parameters and are suitable for users analyzing data for the first time in the tool. We will also show how advanced users can customize pipelines and share them with other Strand NGS users. Finally, we will show a brief glimpse of an elaborate pipeline that aligns reads, filters poor-quality matches, computes coverage metrics, identifies variants, checks for sample cross-contamination, and emails quality reports - all from within Strand NGS.

Speaker: Dr. Vamsi Veeramachaneni, Vice President - Bioinformatics, Strand Life Sciences

Details: Session 1: 2:30 PM IST, Session 2 : 10:30 PM IST
Register here: http://www.strand-ngs.com/webinar_registration

Scribl : HTML5 canvas genomics graphic library

Jit — Thu, 25 Oct 2018 09:38:53 -0500

Scribl is a javascript, Canvas-based graphics library that easily generates biological visuals of genomic regions, alignments, and assembly data. Scribl can also be used in conventional offline pipelines, since everything needed to generate charts can be contained in a single html file.

Address of the bookmark: http://chmille4.github.io/Scribl/

Nucleus: Python and C++ code for reading and writing genomics data.

Jit — Sun, 02 Feb 2020 08:14:19 -0600

Nucleus is a library of Python and C++ code designed to make it easy to read, write and analyze data in common genomics file formats like SAM and VCF. In addition, Nucleus enables painless integration with the TensorFlow machine learning framework, as anywhere a genomics file is consumed or produced, a TensorFlow tfrecords file may be used instead.

Address of the bookmark: https://github.com/google/nucleus

Fully funded position as PhD Research Fellow in genomics/bioinformatics

Wed, 03 Feb 2021 04:18:57 -0600

A fully funded position as PhD Research Fellow in genomics/bioinformatics is available at the Section for Genetics and Evolutionary Biology (EVOGENE) at the Department of Biosciences, University of Oslo.

The fellowship will be for a period of 3 years, or for a period of 4 years, with 25 % compulsory work (e.g. teaching responsibilities at the department) contingent on the qualifications of the candidate and the teaching needs of the department.

Starting date no later than October 1, 2021.

More at https://www.jobbnorge.no/en/available-jobs/job/199984/phd-research-fellow-in-genomics-and-bioinformatics

Tetra-Nucleotide Analysis

Jit — Thu, 04 May 2017 05:07:41 -0500

A tetra-nucleotide is a fragment of DNA sequence with 4 bases (e.g. AGTC or TTGG). Pride et al. (2003) showed that the frequency of tetra-nucleotides in bacterial genomes contain useful, albeit weak, phylogenetic signals. Even though tetra-nucleotide analysis (TNA) utilizes the information of whole genome, it is evident that it cannot replace other alignment-based phylogenetic methods such as OrthoANI or 16S rRNA phylogeny. However, TNA can be useful for phylogenetic characterization when whole genome or 16S rRNA gene information is not available. For example, a partial genomic fragment obtained from a metagenome can be identified by TNA (Teeling et al., 2004). TNA is also fast enough that it can be used as a search engine against a large genome database.

Address of the bookmark: https://chunlab.wordpress.com/tetra-nucleotide-analysis/

Snippy: Rapid haploid variant calling and core SNP phylogeny

Neel — Sat, 11 Aug 2018 11:06:56 -0500

Snippy finds SNPs between a haploid reference genome and your NGS sequence reads. It will find both substitutions (snps) and insertions/deletions (indels). It will use as many CPUs as you can give it on a single computer (tested to 64 cores). It is designed with speed in mind, and produces a consistent set of output files in a single folder. It can then take a set of Snippy results using the same reference and generate a core SNP alignment (and ultimately a phylogenomic tree).

snippy --cpus 16 --outdir mysnps --ref Listeria.gbk --R1 FDA_R1.fastq.gz --R2 FDA_R2.fastq.gz

Address of the bookmark: https://github.com/tseemann/snippy

Mike Ritchie Lab

Wed, 02 Oct 2013 15:25:45 -0500

Mike Ritchie Lab primary research focus is the detection of susceptibility genes for common diseases such as cancer, diabetes, hypertension, and cardiovascular disease, among others. The approaches will involve the development and application of new statistical methods with a focus on the detection of gene-gene interactions associated with human disease.

Gene expression and protein expression patterns between normal and non-normal tissues is a growing area of research that may lead to the identification of candidate genes for understanding the etiology of common, complex diseases.

Lab homepage @ http://ritchielab.psu.edu/ritchielab/