BOL: Related items

Surrogate Variable Analysis (SVA)

Jit — Thu, 30 Oct 2014 08:01:58 -0500

The sva package contains functions for removing batch effects and other unwanted variation in high-throughput experiment. Specifically, the sva package contains functions for the identifying and building surrogate variables for high-dimensional data sets. Surrogate variables are covariates constructed directly from high-dimensional data (like gene expression/RNA sequencing/methylation/brain imaging data) that can be used in subsequent analyses to adjust for unknown, unmodeled, or latent sources of noise. The sva package can be used to remove artifacts in three ways:

(1) identifying and estimating surrogate variables for unknown sources of variation in high-throughput experiments (Leek and Storey 2007 PLoS Genetics,2008 PNAS),

(2) directly removing known batch effects using ComBat (Johnson et al. 2007 Biostatistics) and

(3) removing batch effects with known control probes (Leek 2014 biorXiv).

Removing batch effects and using surrogate variables in differential expression analysis have been shown to reduce dependence, stabilize error rate estimates, and improve reproducibility, see (Leek and Storey 2007 PLoS Genetics, 2008 PNAS or Leek et al. 2011 Nat. Reviews Genetics).

More at http://www.bioconductor.org/packages/release/bioc/html/sva.html

Zhang Lab

Sun, 28 Dec 2014 12:43:08 -0600

We develop and use integrative bioinformatics approaches to extract biological meanings from experimental data and generate hypotheses for experimental validation. Please explore our website to learn more about our people and our research.

More at http://bioinfo.vanderbilt.edu/zhanglab/

Narcis Fernandez-Fuentes Lab

Mon, 25 May 2015 07:30:00 -0500

Welcome to our web-site compiling all the research-related activities of the group. Our research interests relate to a number of areas within Bioinformatics. We have a long-standing interest in protein structure prediction and structure-to-function relationships. We work in the study of biomolecular interactions, modeling of protein complexes, the study and characterization of protein-protein interactions, peptide design, modeling of genetic variation, structure-based protein design and different aspects of Plant Bioinformatics. Take a look at the our databases and servers and the list of publications for more information.

More at http://www.bioinsilico.org/

X. Shirley Liu Lab

Tue, 26 May 2015 17:28:23 -0500

The research in our laboratories are focused on the following three areas:

Bioinformatics
Cancer
Epigenetics

More at http://liulab.dfci.harvard.edu/

BISR Jaipur

Tue, 07 Jul 2015 23:12:26 -0500

The Bioinformatics Centre at BISR has created an infrastructure for providing facilities to the users working in the field of Biological Sciences. The users of Rajasthan, Jaipur in particular, are using facilities available at the Bioinformatics Centre extensively. The centre has leased line Internet connection as well latest Bioinformatics software for sequence and structure analysis. The centre provides the following services:

Bioinformatics supports to researchers
Customized training in Bioinformatics for researchers and faculty members
Support in Installing, implementing and maintaining software on computer.
Create awareness for taking preventive measure against data security
Organize workshops on thrust ares of Bioinformatics
Research Training to students of Biotechnology and Bioinformatics

More at http://bioinfo.bisr.res.in/index.php

liftover

Jitendra Narayan — Mon, 08 Feb 2016 15:45:03 -0600

Convenient conversions between genome assemblie. The liftover package makes it easy to remap genomic coordinates to a different genome assembly.

More at https://github.com/aaronwolen/liftover

https://www.bioconductor.org/help/workflows/liftOver/

Address of the bookmark: https://github.com/aaronwolen/liftover

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

Visiting Scientist - Computational Genomics

Mon, 17 Jul 2017 07:20:18 -0500

ICRISAT is a non-profit, non-political organization that conducts agricultural research for development in Asia and sub-Saharan Africa with a wide array of partners throughout the world. ICRISAT and its partners help empower those living in the semi-arid tropics, especially smallholder farmers, to overcome poverty, hunger, malnutrition and a degraded environment through more efficient and profitable agriculture.

ICRISAT is headquartered in Patancheru near Hyderabad, India, with two regional hubs and five country offices in sub-Saharan Africa. ICRISAT, established in 1972, is a member of the CGIAR Consortium. For more details, see www.icrisat.org.

Job Responsibilities:
Planning and execution of different NGS/genomics data analysis
Apply, maintain, and support cutting-edge pipelines for the analysis and interpretation of NGS data
Analyze large-scale genomic datasets generated internally and through collaboration with others
Genome wide analysis- LD analysis, hapmap, genetic map construction and qtl mapping
Expression analysis based on RNA-seq, gene ontology and metabolic pathway data
Sequence level analysis like gene family analysis, orthology/paralogy etc.
Familiarity with genomic and biological information databases
Compilation and interpretation of results and writing reports
Experience working independently and in a team environment
Requirements:

PhD or M.Sc with 2-3 years experience from reputed institute in the area of life science or similar Knowledge in Next Generation Sequencing (NGS) data analysis. Should be familiar with various sequencing platforms. Sound knowledge of genomics and molecular biology is must. Proficient in any one of the programming/scripting in languages: Python, Perl, PHP, R, Shell Scripting. Must be experienced in working on Linux and CLI environment. Ability to work as team as well as independently with minimal support. Fluency in spoken and written English is essential.

NGS techniques like sequence alignment, variant calling based on whole genome re-sequencing and genotyping-by-sequencing (GBS), RNA-Seq/transcriptome analysis
Knowledge of various standard NGS related tool
Ability to solve complex problems in advanced genomics research areas
Ease and interest in working with people from diverse backgrounds
Excellent oral/written communication and interpersonal/networking skills
General:
This position is contract for a period of two years.

How to apply:
Applicants should apply on or before 27-July-2017, with latest Curriculum Vitae, and the names and contact information of three references that are knowledgeable about your professional qualifications and work experience. All applications will be acknowledged, however only short listed candidates will be contacted
Please CLICK HERE to submit your application.
ICRISAT is an equal opportunity employer

http://icrisat.careersitemanager.com/job-listings-Visiting-Scientist-Computational-Genomics-ICRISAT-Hyderabad-Secunderabad-2-to-4-years-060717000278

Suisse Life Science Group

Rahul Agarwal — Sun, 07 Jan 2018 14:42:23 -0600

THE WORLD’S MOST UNIQUE HEALTH & WELLNESS SERVICE:

AI and science working together to manage the root causes of your aging

Personalized plan built from your biomarkers and devices

Biologically-active treatments (cellular health). No drugs.

Source is Linkedln link :

https://www.linkedin.com/company/5143768/

Address of the bookmark: https://suisselifescience.com/

DEPARTMENT OF GENETICS, GENOMICS AND BIOINFORMATICS, National Biotechnology Development Agency, Nigeria

BioStar — Wed, 05 Sep 2018 10:48:25 -0500

The Genetics, Genomics & Bioinformatics Department (GBBD) at NABDA is unique, encompassing all facets of modern genetics and bioinformatics research. Trans-disciplinary research being conducted in our laboratories would lead to cures for human diseases; improvements to crop and livestock quality and yield; creation of new technologies with applications to medicine; agriculture; environment; and industry.

Our capacity building activities covers both general and specialized topics in translational genetics, and is designed to better acquaint scientists and clinicians with the tools and technologies of genetics and genomics.

OUR RESEARCH ACTIVITIES INCLUDE:

Biomedical Genetics: investigating genetic and environmental factors contributing to phenotypes with relevance to human health and disease.
Computation and Bioinformatics: develop new approaches for the management, analysis, and modelling of large, complex data sets.
Population and Quantitative Genetics: study of how genetic processes evolve to generate genetic variation in populations of organisms, and the effects on the patterning of variation within and between populations and specie, and
Genetic Engineering and Biotechnology: focuses on the research and innovation for industrial enzymes, biologics and biosimilars production.

https://www.h3abionet.org/nabda

Address of the bookmark: http://www.nabda.gov.ng/departments/genetics-genomics-and-bioinformatics