BOL: Related items

Genomics for Bioinformatician

Jitendra Narayan — Sat, 20 Jul 2013 07:03:00 -0500

Genomics is the study of the genomes of organisms. The field includes intensive efforts to determine the entire DNA sequence of organisms and fine-scale genetic mapping efforts. The field also includes studies of intragenomic phenomena such as heterosis, epistasis, pleiotropy and other interactions between loci and alleles within the genome. In contrast, the investigation of the roles and functions of single genes is a primary focus of molecular biology or genetics and is a common topic of modern medical and biological research. Research of single genes does not fall into the definition of genomics unless the aim of this genetic, pathway, and functional information analysis is to elucidate its effect on, place in, and response to the entire genome's networks.

Genomics was established by Fred Sanger when he first sequenced the complete genomes of a virus and a mitochondrion. His group established techniques of sequencing, genome mapping, data storage, and bioinformatic analyses in the 1970-1980s. A major branch of genomics is still concerned with sequencing the genomes of various organisms, but the knowledge of full genomes has created the possibility for the field of functional genomics, mainly concerned with patterns of gene expression during various conditions. The most important tools here are microarrays and bioinformatics. Study of the full set of proteins in a cell type or tissue, and the changes during various conditions, is called proteomics. A related concept is materiomics, which is defined as the study of the material properties of biological materials (e.g. hierarchical protein structures and materials, mineralized biological tissues, etc.) and their effect on the macroscopic function and failure in their biological context, linking processes, structure and properties at multiple scales through a materials science approach. The actual term 'genomics' is thought to have been coined by Dr. Tom Roderick, a geneticist at the Jackson Laboratory (Bar Harbor, ME) over beer at a meeting held in Maryland on the mapping of the human genome in 1986.

The outcome of almost two years of intense discussions with literally hundreds of scientists and members of the public, has three major areas of focus: Genomics to Biology, Genomics to Health, and Genomics to Society.

Genomics to Biology:
The human genome sequence provides foundational information that now will allow development of a comprehensive catalog of all of the genome's components, determination of the function of all human genes, and deciphering of how genes and proteins work together in pathways and networks.

Genomics to Health:
Completion of the human genome sequence offers a unique opportunity to understand the role of genetic factors in health and disease, and to apply that understanding rapidly to prevention, diagnosis, and treatment. This opportunity will be realized through such genomics-based approaches as identification of genes and pathways and determining how they interact with environmental factors in health and disease, more precise prediction of disease susceptibility and drug response, early detection of illness, and development of entirely new therapeutic approaches.

Genomics to Society:
Just as the HGP has spawned new areas of research in basic biology and in health, it has created new opportunities in exploring the ethical, legal, and social implications (ELSI) of such work. These include defining policy options regarding the use of genomic information in both medical and non-medical settings and analysis of the impact of genomics on such concepts as race, ethnicity, kinship, individual and group identity, health, disease, and "normality" for traits and behaviors.

This vision for the future of genomics is not just about the NHGRI. It encompasses the whole field of genomics, including the work of all the other Institutes and Centers at the NIH and of a number of other federal agencies. All of the NIH Institutes are already taking full advantage of the sequence and will apply its data to the better understanding of both rare and common diseases, almost all of which have a genetic component. A recent example of the way that the HGP and the knowledge and new technologies it has spawned are already facilitating science is the extremely rapid sequencing by groups in Canada and at the Centers for Disease Control and Prevention (CDC) in Atlanta of the genome of the virus that causes Severe Acute Respiratory Syndrome (SARS). The sequencing of the SARS virus genome provides insight into this new and deadly disease at a speed never before possible in science. In turn, this should lead to the rapid development of diagnostic tests and, in time, vaccines and effective treatments.

Links for the addition material available on Net

Genomes and genomics:

Bioinformatics and Genomics:

Structural genomics tutorial:

Comparative Genomics Tutorial:

GENOME TUTORIAL:

Tools and resources for identifying protein families, domains and motifs

Bioinformatics Tools
Tips, Tutorials, and Terminology for Using Selected Resources in Genome Database Guide:

A Web-Based Comparative Genomics Tutorial for Investigating Microbial Genomes:

Free Online Tutorials Teach Anyone How to Use Genome Databases:

Circos to create concise, explanatory, unique and print-ready visualizations of your data:

Genomics and Comparative Genomics Learning Module:

Computational Challenges in Comparative Genomics

A Tutorial:

A Comparative Genomics Resource for Grains:

PLAZA: A Comparative Genomics Resource to Study Gene and Genome Evolution in Plants:

VISTA :

Software for Genomics

Artemis Artemis is a free genome viewer and annotation tool that allows visualization of sequence features and the results of analyses within the context of the sequence, and its six-frame translation.
Chromas It will display and prints chromatogram files from ABI automated DNA sequencers, and Staden SCF files which the analysis programs for ALF, Li-Cor and Visible Genetics OpenGene sequencers can create.
Glimmer A system for finding genes in microbial DNA, especially the genomes of bacteria and archaea.Glimmer (Gene Locator and Interpolated Markov Modeler) uses interpolated Markov models (IMMs) to identify the coding regions and distinguish them from noncoding DN
Glimmer HMM A fast and accurate gene finder based on a GHMM architecture, developed specifically for eukaryotes. It incorporates splice site models adapted from the GeneSplicer program and uses interpolated Markov models for evaluating the coding regions.
Glimmer M A gene finder derived from Glimmer, but developed specifically for eukaryotes. It is based on a dynamic programming algorithm that considers all combinations of possible exons for inclusion in a gene model and chooses the best of these combinations. The d
MUMmer MUMmer is a system for rapidly aligning entire genomes, whether in complete or draft form.
pDRAW pDRAW32 is being developed as a free time hobby project. It is far from finished, but as it has reached a point where it could be helpful for many labs, it is now available to the scientific community.
Sequin Sequin is a stand-alone software tool developed by the NCBI for submitting and updating entries to the GenBank, EMBL, or DDBJ sequence databases. It is capable of handling simple submissions that contain a single short mRNA sequence, and complex submissio
Staden The Staden Package consists of a series of tools for DNA sequence preparation (pregap4), assembly (gap4), editing (gap4) and DNA/protein sequence analysis (spin).

For more software @ http://bioinformaticsonline.com/bookmarks/view/926/list-of-popular-bioinformatics-softwaretools

Bienko and Crosetto Labs

Fri, 12 May 2017 07:42:15 -0500

We are two groups of scientists doing frontier research in quantitative biology and biomedicine. The Bienko group is interested in exploring the fundamental design principles controlling how DNA is packed in the eukaryotic nucleus and its relation to gene expression regulation. The Crosetto group engineers new molecular methods for single-cell and spatially resolved omic measurements of DNA, RNA, and proteins, with a strong focus on tumor heterogeneity. By sharing ideas and resources, we work synergistically towards a more quantitative understanding of life’s processes in healthy and diseased conditions.

https://bienkocrosettolabs.org/

Research with help of bioinformatics helpful

Jit — Fri, 02 Aug 2013 11:20:24 -0500

Endocrinologist G.R. Sridhar says

Research with the help of bioinformatics with a trans-disciplinary approach is yielding good results.
http://www.thehindu.com/features/education/research/research-with-help-of-bioinformatics-helpful/article2295629.ece

Salzberg lab

Mon, 15 May 2017 05:14:01 -0500

We are a computational biology lab that develops novel methods for analysis of DNA and RNA sequences. Our research includes software for aligning and assembling RNA-seq data, whole-genome assembly, and microbiome analysis. We work closely with biomedical scientists to apply these methods to current problems arising in a broad spectrum of biological and medical research areas. We’re also part of the Center for Computational Biology, a group of 20+ faculty members and their labs at Johns Hopkins working on computational, statistical, and mathematical methods that can turn massive genomic data sets into biologically and clinically useful information.

https://salzberg-lab.org/

NCBI Prokaryotic Genome Annotation Pipeline

Jit — Tue, 16 May 2017 08:56:03 -0500

NCBI Prokaryotic Genome Annotation Pipeline is designed to annotate bacterial and archaeal genomes (chromosomes and plasmids).

Genome annotation is a multi-level process that includes prediction of protein-coding genes, as well as other functional genome units such as structural RNAs, tRNAs, small RNAs, pseudogenes, control regions, direct and inverted repeats, insertion sequences, transposons and other mobile elements.

NCBI has developed an automatic prokaryotic genome annotation pipeline that combines ab initio gene prediction algorithms with homology based methods. The first version of NCBI Prokaryotic Genome Automatic Annotation Pipeline (PGAAP; see Pubmed Article) developed in 2005 has been replaced with an upgraded version that is capable of processing a larger data volume. You can find a more detailed description of the new version of the pipeline in NCBI Handbook chapter. NCBI's annotation pipeline depends on several internal databases and is not currently available for download or use outside of the NCBI environment.

https://www.ncbi.nlm.nih.gov/genome/annotation_prok/

Address of the bookmark: https://www.ncbi.nlm.nih.gov/genome/annotation_prok/

Senior Bioinformatics Software Developer, Hyderabad, Telangana

Mon, 03 Jul 2017 10:10:31 -0500

DuPont Pioneer is the world leader in plant biotechnology area including discovery, development and delivery of elite crop genetics. DuPont Pioneer is aggressively building Big Data and Predictive Analytics capabilities in order to deliver improved services to our customers. We are currently seeking Senior Bioinformatics Software Developer at the DuPont Knowledge Center in Hyderabad, India for our global Data Science and Informatics group. At DuPont Pioneer, you’ll become part of a work environment that nurtures your interests, ignites your passion, creates opportunities to serve and helps you attain success–both personally and professionally. The hiring level will be commensurate with the level of experience. This is a critical position with the potential to make immediate, significant impact on our business.
The successful candidate will have an extensive background in computer science and bioinformatics through courses or academic degrees, and proven experience in bioinformatics software development. We are looking for those creative, smart, model driven, agile individuals who enjoy giving their all to tackle diverse software needs.
Duties / Responsibilities

Job Qualifications
Education and Experience
• Master Degree in Bioinformatics, Computational biology, Scientific Computing or related field
• 3-5 years of Post-Master’s experience in Bioinformatics software development
• Proven experience developing high throughput bioinformatics applications
Required Competencies
• Strong proven experience in Python programming language in Linux environment
• Proven High Performance computing experience (LSF/SGE/OGE)
• Exposure in code versioning and repository management (GIT/SVN)
• Proven experience in Bioinformatics algorithm development
• Deep understanding in Bioinformatics tools, data types
Desired Competencies
• Familiarity working in a scientific computing environment (NumPy, SciPy, Pandas etc.)
• Familiarity working with Cloud technologies (AWS, Azure)
• Ability to demonstrate solid analytical skills and exceptional attention to detail.
• Experience in relational databases and data structures
• Proven experience working with teams using agile software development methodologies and processes
• Familiarity with Service Oriented Architecture (SOA)
• Familiarity with build tools (Jenkins, make, ANT, Maven)
• Exposure to project management tools (JIRA, Confluence, RED MINE, etc.)

More at http://careers.dupont.com/jobsearch/job-details/senior-bioinformatics-software-developer/012939W-01/

2013 NextGen Genomics & Bioinformatics Technologies (NGBT) Conference, New Delhi, INDIA

Thu, 08 Aug 2013 16:21:16 -0500

2013 NextGen Genomics & Bioinformatics Technologies (NGBT) Conference

SciGenom Research Foundation (SGRF) and Institute of Genomics and Integrative Biology (IGIB) are pleased to host the Next-Generation Sequencing and Bioinformatics for Genomics & Healthcare conference.

In the ten years since the first human reference genome was completed for US$3 billion the sequencing technologies have radically changed leading to great reduction in sequencing cost. Today a human genome can be sequenced for under US$ 5000 in less than two weeks. It is expected that by the end of 2015 the cost of sequencing a human genome will drop to below thousand dollars. The next generation sequencing technologies over the past five years have enabled a large number of genomic studies that impact human health and disease. Also, this has made possible the growth of microbial, animal and plant genomics studies. While the data production has increased at a rapid pace challenges remain in analyzing and understanding the data. The conference will cover the next generation sequencing (NGS) technologies, bioinformatics for NGS and applications of NGS in many areas including personalized medicine.

For more info : http://www.scigenomconferences.com/2013/default.php

The 10th North East Bioinformatics Network (NEBINet) Annual Coordinators' Meet

Jit — Sat, 18 Nov 2017 15:02:44 -0600

The 10th North East Bioinformatics Network (NEBINet) Annual Coordinators' Meet organised by the Bioinformatics Centre, St Edmund's College, Shillong and sponsored by the Department of Biotechnology, Government of India, was held at St Edmund's College Auditorium here on Thursday. Meghalaya Governor Ganga Prasad graced the inaugural programme as chief guest.
In his inaugural address, the Governor said the panorama of scientific scenario has greatly changed over the years, the thrust areas have undergone a metamorphosis but the conceptual underpinning of the basic sciences still continues.
"Of late, the activity of basic research has been intricately intertwined with technology. And we are determined to carry forward this change, for it is through technology that science can actually reach the masses in our country and afar, and the changing times have also inculcated a culture of cross-departmental and interdisciplinary research. Science and technology has always played a pivotal role in taking a nation towards greater heights by ways of innovations and inventions," he added.
Prasad also hoped that discussions, suggestions and sharing of innovative ideas during the two-day 10th NEBINet Annual Coordinators' Meet will open up new avenues to make substantial advancement in Biological Sciences which will provide a platform for proper and effective delivery mechanism for the common man.
During the inaugural function, Advisor of Department of Biotechnology Dr T Madhan Mohan gave an overview of the NEBINet and Bioinformatics programme.
President of Epygen Biotech FZ LLC, Dubai, UAE, Dr Debayan Ghosh, delivered the keynote address.
St Edmund's College governing body secretary Brother Simon Coelho and St Edmund's College Principal Dr Sylvanus Lamare also spoke during the function.

Postdoctoral Associate - Bioinformatics at Duke University Medical Center

Sat, 10 Aug 2013 18:38:38 -0500

The Department of Biostatistics and Bioinformatics at Duke University Medical Center is seeking a Postdoctoral Associate for a one year appointment to work on several high-dimensional research projects. The specific goals of the project are to identify genes or molecular markers that are predictive of clinical outcomes in renal and prostate cancer.

Candidates must have: a PhD degree in statistics, biostatistics or bioinformatics, extensive experience in analyzing high-dimensional data (microarray, SNP, CNVs) and of validation approaches. In addition, experience in penalized regression methods, data base manipulation; and strong programming skills in order to conduct Monte Carlo studies and applications (R). Candidate must have excellent communication skills (verbal, written and presentation), a strong proficiency in Linux system.

This position is available immediately and will be filled as soon as possible. Appointment could be extended beyond the first year based on additional funding.

For more information about the Department of Biostatistics and Bioinformatics, please visit our website: http://www.biostat.duke.edu.

For more info: http://biostat.duke.edu/sites/biostat.duke.edu/files/Halabi%20-%20Postdoc%20Job%20Posting%202013%20updated.pdf

Duke University is an Equal Opportunity/Affirmative Action Employer.

Bioinformatics tools developed for Oxford Nanopore data analysis !

biogeek — Wed, 27 Dec 2017 20:47:30 -0600

MinION is the only portable real-time device for DNA and RNA sequencing. Each consumable flow cell can now generate 10–20 Gb of DNA sequence data. Ultra-long read lengths are possible (hundreds of kb) as you can choose your fragment length. One of the technical advantages of ONT data is the read length, which offers great prospects for genome assembly. Generally, assemblers are based on several different types of algorithms, such as greedy, overlap-layout-consensus (OLC), de Bruijn graph (DBG), and string graph.

List of analysis tools developed for Oxford Nanopore data

BWA
Fast nanopore data tuned alignment tool
https://github.com/lh3/bwa

GraphMap
Mapper for long and error-prone reads
https://github.com/isovic/graphmap

LAST
Nanopore tuned alignment tool
http://last.cbrc.jp/

LINKS
Software tool for long read scaffolding
https://github.com/warrenlr/LINKS/

marginAlign
Tools to align nanopore reads to a reference
https://github.com/benedictpaten/marginAlign

minoTour
Real time analysis tools
http://minotour.nottingham.ac.uk/

nanoCORR
Error-correction tool for nanopore sequence data
https://github.com/jgurtowski/nanocorr

NanoOK
Software for nanopore data, quality and error profiles
https://documentation.tgac.ac.uk/display/NANOOK/NanoOK

Nanopolish
Nanopore analysis and genome assembly software
https://github.com/jts/nanopolish

nanopore
Variant-detection tool for nanopore sequence data
https://github.com/mitenjain/nanopore

Nanocorrect
Error-correction tool for nanopore sequence data
https://github.com/jts/nanocorrect/

npReader
Real-time conversion and analysis of nanopore reads
https://github.com/mdcao/npReader

poRe
Tool for analyzing and visualizing nanopore data
https://sourceforge.net/p/rpore/wiki/Home/

PoreSeq
Error-correction and variant-calling software
https://github.com/tszalay/poreseq

Poretools
Nanopore sequence analysis and visualization software
https://github.com/arq5x/poretools

SSPACE-LongRead
Genome scaffolding tool
http://www.baseclear.com/genomics/bioinformatics/basetools/SSPACE-longread

SMIS
Genome scaffolding tool
https://sourceforge.net/projects/phusion2/files/smis/

List of assemblers for Oxford Nanopore MinION long reads

LQS
DALIGNER, Celera OLC Nanocorrect,
Nanopolish corrector
https://github.com/jts/nanopolish

PBcR
HGAP or BLASR, Celera OLC
PBcR corrector
http://wgs-assembler.sourceforge.net/wiki/index.php/PBcR
–
Canu
MHAP, Celera OLC
Canu corrector
https://github.com/marbl/canu

Falcon
String graph, Celera OLC
Falcon corrector
https://github.com/PacificBiosciences/falcon

Miniasm
OLC
https://github.com/lh3/miniasm

ra-integrate
OLC
https://github.com/mariokostelac/ra-integrate/

ALLPATHS-LG
de Bruijn graph
ALLPATHS-L corrector
https://www.broadinstitute.org/software/allpaths-lg/blog/?page_id=12

SPAdes
de Bruijn graph
SPAdes corrector
http://bioinf.spbau.ru/spades