BOL: Related items

ArrayGen Bioinformatics Genomics Group

Sun, 28 Sep 2014 14:09:55 -0500

ArrayGen is a global bioinformatics company which is a one stop solution for microarray designing and genomics data analysis. Our novel Array Design Approach Strategy (ADAS) aims to condense the time lag between demands of scientific community and manufacture industry, thereby expediting research processes.

ArrayGen specializes in Genomics data analysis and research, as we believe in the level of precision, predictability, benchmark-ability, and data analysis capability of genomics data over other forms of biological data. ArrayGen constantly strives to develop new solutions, and plug the existing gaps in the technological advancement of the field.

More http://www.arraygen.com/

Computational Genomics: Applied Comparative Genomics

Jit — Wed, 29 Nov 2017 05:11:30 -0600

The primary goal of the course is for students to be grounded in theory and leave the course empowered to conduct independent genomic analyses. We will study the leading computational and quantitative approaches for comparing and analyzing genomes starting from raw sequencing data. The course will focus on human genomics and human medical applications, but the techniques will be broadly applicable across the tree of life. The topics will include genome assembly & comparative genomics, variant identification & analysis, gene expression & regulation, personal genome analysis, and cancer genomics. The grading will be based on assignments, a midterm exam, class presentations, and a significant class project. There are no formal course prerequisites, although the course will require familiarity with UNIX scripting and/or programming to complete the assignments and course project.

Address of the bookmark: https://github.com/schatzlab/appliedgenomics

Method in Comparative genomics !!

Jit — Wed, 09 Nov 2016 16:29:24 -0600

We present methods for the automatic determination of genome correspondence. The algorithms enabled the automatic identification of orthologs for more than 90% of genes and intergenic regions across the four species despite the large number of duplicated genes in the yeast genome. The remaining ambiguities in the gene correspondence revealed recent gene family expansions in regions of rapid genomic change.

We present methods for the identification of protein-coding genes based on their patterns of nucleotide conservation across related species. We observed the pressure to conserve the reading frame of functional proteins and developed a test for gene identification with high sensitivity and specificity. We used this test to revisit the genome of S. cerevisiae, reducing the overall gene count by 500 genes (10% of previously annotated genes) and refining the gene structure of hundreds of genes. We present novel methods for the systematic de novo identification of regulatory motifs. The methods do not rely on previous knowledge of gene function and in that way differ from the current literature on computational motif discovery. Based on the genome-wide conservation patterns of known motifs, we developed three conservation criteria that we used to discover novel motifs. We used an enumeration approach to select strongly conserved motif cores, which we extended and collapsed into a small number of candidate regulatory motifs. These include most previously known regulatory motifs as well as several noteworthy novel motifs. The majority of discovered motifs are enriched in functionally related genes, allowing us to infer a candidate function for novel motifs.

Our results demonstrate the power of comparative genomics to further our understanding of any species. Our methods are validated by the extensive experimental knowledge in yeast, and will be invaluable in the study of complex genomes like that of human.

Address of the bookmark: http://web.mit.edu/manoli/www/publications/Kellis_JCB_04.pdf

DIYA: a bacterial annotation pipeline for any genomics lab

Jit — Fri, 30 Jun 2017 08:48:26 -0500

DIY Genomics is an open source bioinformatics consortium intended to bring a collection of tools and libraries into the hands of small scale genomics labs for the process of sequence assembly and annotation. Projects include DIYA, MGAP, CRISPR, and DIYGV

http://gmod.org/wiki/Diya

Address of the bookmark: https://sourceforge.net/projects/diyg/

MetaSim A Sequencing Simulator for Genomics and Metagenomics.

Jit — Mon, 04 Dec 2017 07:18:20 -0600

Our software can be used to generate collections of synthetic reads that reflect the diverse taxonomical composition of typical metagenome data sets. Based on a database of given genomes, the program allows the user to design a metagenome by specifying the number of genomes present at different levels of the NCBI taxonomy, and then to collect reads from the metagenome using a simulation of a number of different sequencing technologies. A population sampler optionally produces evolved sequences based on source genomes and a given evolutionary tree.

Address of the bookmark: http://ab.inf.uni-tuebingen.de/software/metasim/

Bioinformatics jobs at NIBMG

Wed, 16 May 2018 02:57:15 -0500

NIBMG are looking for bright and motivated people in our big projects on cutting edge biomedical genomics research

http://www.nibmg.ac.in/academic/SyMeC-ICGC/SyMeC%20&%20ICGC_May%202018.pdf

http://www.nibmg.ac.in/academic/plp/15_05_2018/AdvertisementMay2018.pdf

ComparativeGenomics Exercise2

Neel — Wed, 22 Aug 2018 22:10:56 -0500

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

The Global Alliance for Genomics and Health (GA4GH)

Jit — Sat, 08 Feb 2020 07:37:31 -0600

The Global Alliance for Genomics and Health (GA4GH) is a policy-framing and technical standards-setting organization, seeking to enable responsible genomic data sharing within a human rights framework.

GA4GH core funders and sponsors enable our work and allow us to convene the international genomic data sharing community.

https://www.ga4gh.org/

Address of the bookmark: https://www.ga4gh.org/

Comparative Genomics Data Set Including 240 Mammals Released !

Jit — Thu, 19 Nov 2020 06:45:39 -0600

The genome of 130 mammals was sequenced by a large international consortium and the data was analyzed together with 110 existing genomes to allow scientists to identify the important positions in the DNA. This report, published in Nature today will help advance research on human disease mutations and inform how best to protect endangered species.

In addition to the knowledge of the human genome, all these genomes, widely sampled across mammals, can be used to research how particular organisms respond to different conditions. Some otters, for example, have a thick, water-resistant shell, and some rodents, but not all, have adapted to hibernation. These animal traits will help us to understand human traits, such as metabolic diseases.

With climate change and more animal ecosystems being threatened by human activity, the protection of endangered species is becoming increasingly important. Scientists have historically researched several people in various populations of a species to understand the genetic variation that occurs in that species. This is important for understanding how particular species can be protected. In this study, animals on the Red List of Endangered Species of the International Union for Conservation of Nature had fewer differences in their genomes, which is consistent with their endangered status.

Ref @ A comparative genomics multitool for scientific discovery and conservation https://www.nature.com/articles/s41586-020-2876-6

Data at http://zoonomiaproject.org/

Scientist C - Non-Medical (IT Expert- Computer Professional/Genomics/Bioinformatic) at NIMR

Mon, 01 Feb 2021 13:54:06 -0600

Applications are invited upto 12th February 2021 in the prescribed format (available on the websites of ICMR-NIMR) through link http://onlineapply.nimr.org.in/ up to 05:00 PM on 12th February 2021 for the following post on contract basis at NIMR, Sector-8, Dwarka, New Delhi.

Scientist C - Non-Medical (IT Expert- Computer Professional/Genomics/Bioinformatic)No. of posts: 01 (UR)

Salary (Fixed): Rs.51,000/- + HRA

Essential Qualification: Candidate should possess 1st class master degree in relevant subjects from a recognized university with 4 years experience
OR
2nd class M.Sc + Ph.D degree in relevant subjects from a recognized university with 4 years experience.Desirable Qualification: Candidates should possess a PhD degree in any field of science.
Preference will be given to those who have published scientific papers in international journals and who have a track record of working in infectious diseases.

The candidate must know the following for further consideration: (a) data processing and analysis using statistical softwares, (d) programming, (e) presentation of complex data from excel files and related skills.
Understanding of GIS and malaria will be an advantage. Experience and interest in functional genomics and genomic sequencing will be important.

Age Limit: 40 YearsDuration: 30.09.2021

More at http://onlineapply.nimr.org.in/