More at http://ncb.qau.edu.pk/

ADVERTISEMENT NO: NITR/SR/CH-BIF/2014/30

Applications are invited on prescribed format for the following assignment in a purely time bound research project undertaken in the Department of Biotechnology & Medical Engineering of the Institute.

1. Name of the Temporary Post : Senior Research Fellow-01
2. Name of the Research Project: “ Bioinformatics Infrastructure Facility (BIF)”
3. Name of the Sponsoring Agency: DBT, Government of India, 4 Tenure of the Project : 12th Five year Plan
5 Tenure of the Assignment : 01 year [Likely to be extended for 04 more years]
6 Job Description : BIF Maintenance and Active Research in Bioinformatics
7. Consolidated monthly compensation / Fellowship: Rs.18,000/- P.M.

8. Essential Qualifications and experience: B.Tech with valid GATE Score or M.Tech degree in Biotechnology/Bioinformatics/Computer Science/Computational Biology
9. Desirable Qualifications/ Experiences: Experience of Programming in PERL,R, Python, Unix and Visual Studio + Knowledge in NGS data analysis work flows ,WGS and statistical packages such as CRAN-R,MATLAB etc.

10. Accommodation : Bachelor accommodation in the Institute may be provided subject to availability.
11. For technical information on the project, the candidate may contact the Principal Investigator at the following address:

Name : Prof. Mukesh K Gupta
Address : Dept. of Biotechnology & Medical Engineering,
N.I.T.Rourkela-769 008
Telephone No : 0661-2462294
E-mail : guptam@nitrkl.ac.in

Eligible persons may apply in the prescribed format (available in the Institute Website)affixed with coloured photographs to be submitted in duplicate along with photo copies of relevant certificates, grade/ mark sheets, publications etc., to Asst. Registrar, SRICCE,
National Institute of Technology, Rourkela–769 008 before 22.08.2014. The cover should be super- scribed clearly the post applied for & Name of the Project.

Mere possession of minimum qualification does not guarantee invitation to the interview.
Candidates will be short listed based on merit and need of the project.

Advertisement:

http://www.nitrkl.ac.in/IntraWeb/Jobs_Tenders/Jobs/ProjectFellowship/2014/141707192838_1.pdf

Address of the bookmark: http://genomethreader.org/

Studentship and Traineeship in Bioinformatics

Applications are invited on plain paper from suitable candidates for Studentship and Traineeship (One each) at Bioinformatics Sub-Center as detailed below:

1. Studentship: Studentship is for those who have completed M. Sc. Degrees in Life Science.

Number of seats : One

Duration : Six months

Eligibility : Passed M.Sc. degree in Life Sciences.

Fellowship : Rs. 5000/- (Five thousand only) per month

2. Traineeship: Traineeship is for those who have completed M. Sc. Degrees in Life Science/Registered Ph. D. student in Life Sciences.

Number of seats : One

Duration : Six months

Eligibility : Passed M.Sc. degree in Life Sciences/ Registered Ph. D. student in Life Sciences

Fellowship : Rs. 5000/- (Five thousand only) per month

Preferences will be given to person who has experience in Bioinformatics and Computer
sciences. The application along with detailed bio-data should reach the undersigned, on or before 25th August 2014. Both, the studentship and the traineeship are temporary, will be discontinued after the six months from the date of Joining. It may be discontinued in-between without any notice, if the work is not found satisfactory.

Advertisement www.bioinfobubpl.nic.in/Advertisement_st.pdf

The vital metaphase stage of cell division, when the sister chromatids migrated to the centre and lined up in a row, and pulled apart using attached microtubules in such a way that half the DNA ends up in each daughter cell. However, before the mitotic spindle‐mediated movement gets start and pulled DNA apart, the chromosomes are free to undergo recombination which involves the exchange of genetic material either between multiple chromosomes or between different regions of the same chromosome.

During recombination, the precise breakage of each strand, exchange between the strands, and sealing of the resulting recombined molecules happens. The “chromosomal breakpoints” refers to these places where they break. Mostly, this process occurs with a high degree of accuracy at high frequency in both eukaryotic and prokaryotic cells. But occasionally this “break and sealing/ break and reattach” process goes wrong and the reattachment happens in the wrong place which usually create disaster (with few exceptions).These chromosome disaster or abnormalities involve the gain, loss or rearrangement of visible amounts of genetic material during cell division. These abnormalities are of two type, the first one is numerical abnormalities  where severe disorders are caused by the loss or gain of whole chromosomes, which affect the copy number of hundreds or even thousands of genes. The second are structural abnormalities which can be unbalanced or balanced. The former are similar to numerical abnormalities in that genetic material is either gained or lost. The natural defects in chromosome segregation are linked to cancer and several genetic diseases (http://en.wikipedia.org/wiki/List_of_genetic_disorders). Therefore, the enzymes involved in regulating cell division are still the attractive drug targets for many diseases.

Apart from certain chromosome abnormalities, these “crossing over” of segments of maternal and paternal chromosomes to form hybrid chromosomes have some evolutionary importance and considered as a driver of genetic variation. Moreover, the chromosome breakage in evolution is considered to be non-random in nature(http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.0020014). In addition the study of breakpoint regions and non-breakpoint (stable) regions of chromosomes indicates both the regions evolved in distinctly different ways ( http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2675965/). These breakage may lead to genetic diseases or participate to chromosomal rearranmgnets and contributed in development of new species.

I will try to explain the genome hotspots/Evolutionary Breakpoint Regions(EBRs)/fragile regions/weak fragments/  in my next blog.

Software for recombination detection:

RAT http://cbr.jic.ac.uk/dicks/software/RAT/

Breakpointer https://github.com/ruping/Breakpointer

DRP http://web.cbio.uct.ac.za/~darren/rdp.html

RB-finder http://www.ncbi.nlm.nih.gov/pubmed/18707535

LDhat2.0 http://ldhat.sourceforge.net/LDhat2.0/instructions.shtml

Reference:

http://www.nature.com/scitable/topicpage/genetic-recombination-514#

Image: Wikipedia , sciencelearn.org.nz

Recommended Articles:

http://www.friendshipcircle.org/blog/2012/05/22/13-chromosomal-disorders-youve-never-heard-of/

http://web.udl.es/usuaris/e4650869/docencia/segoncicle/genclin98/recursos_classe_%28pdf%29/revisionsPDF/chromosyndromes.pdf

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2775595/table/T2/

http://learn.genetics.utah.edu/content/disorders/chromosomal/

http://www.ncert.nic.in/html/learning_basket/biology/cc&cd.pdf

Following are the genome assembly tools based on string graph:

1.SGA (String Graph Assembler) https://github.com/jts/sga

Assembles large genomes from high coverage short read data. SGA is designed as a modular set of programs, which are used to form an assembly pipeline. SGA implements a set of assembly algorithms based on the FM-index. As the FM-index is a compressed data structure, the algorithms are very memory efficient. The SGA assembly has three distinct phases. The first phase corrects base calling errors in the reads. The second phase assembles contigs from the corrected reads. The third phase uses paired end and/or mate pair data to build scaffolds from the contigs. The output of this software is a PDF report that allows the properties of the genome and data quality to be visually explored. By providing more information to the user at the start of an assembly project, this software will help increase awareness of the factors that make a given assembly easy or difficult, assist in the selection of software and parameters and help to troubleshoot an assembly if it runs into problems.

2. SAGE: String-overlap Assembly of GEnomes https://github.com/lucian-ilie/SAGE2

SAGE, for de novo genome assembly. As opposed to most assemblers, which are de Bruijn graph based, SAGE uses the string-overlap graph. SAGE builds upon great existing work on string-overlap graph and maximum likelihood assembly, bringing an important number of new ideas, such as the efficient computation of the transitive reduction of the string overlap graph, the use of (generalized) edge multiplicity statistics for more accurate estimation of read copy counts, and the improved use of mate pairs and min-cost flow for supporting edge merging. The assemblies produced by SAGE for several short and medium-size genomes compared favourably with those of existing leading assemblers.

3. FSG: Fast String Graph

The new integrated assembler has been assessed on a standard benchmark, showing that fast string graph (FSG) is significantly faster than SGA while maintaining a moderate use of main memory, and showing practical advantages in running FSG on multiple threads. Moreover, we have studied the effect of coverage rates on the running times.

4.  BASE https://github.com/dhlbh/BASE

It enhances the classic seed-extension approach by indexing the reads efficiently to generate adaptive seeds that have high probability to appear uniquely in the genome. Such seeds form the basis for BASE to build extension trees and then to use reverse validation to remove the branches based on read coverage and paired-end information, resulting in high-quality consensus sequences of reads sharing the seeds. Such consensus sequences are then extended to contigs. BASE is a practically efficient tool for constructing contig, with significant improvement in quality for long NGS reads. It is relatively easy to extend BASE to include scaffolding.

5. Fermi https://github.com/lh3/fermi/

Fermi is a de novo assembler with a particular focus on assembling Illumina short sequence reads from a mammal-sized genome. In addition to the role of a typical assembler, fermi also aims to preserve heterozygotes which are often collapsed by other assemblers. Its ultimate goal is to find a minimal set of unitigs to represent all the information in raw reads.

If you want to learn about String Graph assembler, please read the following papers -

i) The Fragment Assembly String Graph - E. W. Myers

This paper describes the String Graph concept.

ii) Efficient construction of an assembly string graph using the FM-index - Jared T. Simpson and Richard Durbin

This earlier paper from Simpson and Durbin

iii) Efficient de novo assembly of large genomes using compressed data structures - Jared T. Simpson and Richard Durbin

Walk in interview for guest faculty in Pondicherry University, India. For more information please visit http://www.bicpu.edu.in/bioinfor140814.pdf

Address of the bookmark: https://github.com/SysBioChalmers/RAVEN

DNAApp: for iPhone/iPad

This is an iOS app that allows for the opening and analysis of DNA sequencing files - ab1. It includes handy tools such as "Reverse Complement", "Jump to", "Copy and Paste sequences", fast and end scrolling, "Chromatogram adjustments", and "Searching for segments" functions.
When used in combination with other zip apps, and also web-tools like Blast, this app allows you to analyze, and also determine the quality of your sequencing files.
This app works with cloud storage access like Dropbox to your sequencing files.
This is now compatible with the new update for iOS 7.1.
Demo video can be found at: https://www.youtube.com/watch?v=mXeo9hXdZgM 

More @ https://itunes.apple.com/us/app/dnaapp/id854944694?mt=8

DNAApp: For android

This is the first android app that allows for the opening and analysis of DNA sequencing files - ab1. It includes handy tools such as "Reverse Complement", "Jump to", fast and end scrolling, "Chromatogram adjustments", amino acid translations, "export to fasta", and "searching for segment" function.

• When used in combination with other zip apps, and also web-tools like Blast, this app allows you to analyze, and also determine the quality of your sequencing files.
• This app works with cloud storage access like Dropbox to your sequencing files.
• This is now compatible with the new update for Android 4.4.2.

More @  https://play.google.com/store/apps/details?id=bii.seqdatreader&hl=en

BioGene:iPhone/iPad

BioGene is an information tool for biological research. Use BioGene to learn about gene function. Enter a gene symbol or gene name, for example "CDK4" or "cyclin dependent kinase 4" and BioGene will retrieve its gene function and references into its function (GeneRIF).

• BioGene was produced in affiliation with the Computational Biology Center at Memorial Sloan-Kettering Cancer Center with primary information from Entrez Gene at the NCBI.

More @  https://itunes.apple.com/us/app/biogene/id333180084?mt=8

Mentha - the interactome browser: Android

About: mentha - the interactome browser, is a project that offers protein-protein physical/enzymatic interaction information from various sources. For more details about mentha, visit mentha's website. This client application is an independent project. This application is designed to allow you to search proteins on the go.

Key features (Also in website):

• Search proteins by UniProt IDs, gene name or keywords
• Collect proteins from different queries.
• Spot common interactors in clusters.
• Easily distinguish between proteins from Homo sapiens and other organisms (Yellow rounded rectangles)
• Click on edges(links) to get scientific evidence.
• Click on proteins to see descriptions.

More @  https://play.google.com/store/apps/details?id=com.sinnefa.mentha&hl=en

GeneIndex: iPhone/iPad

GeneIndex quickly provides information about genes from various sources. It also includes a RSS reader for journal feeds as well as a PubMed viewer.

Key Features:

• Look up genes by symbol or description.
• Gene indexes for many mammals, plants, invertebrates, and bacteria.
• Link to gene info on websites.
• Download files for offline use. (.pdf, .mp3, .m4v, .doc, .ppt, .xls )
• transfer files via open in, email, or iTunes file sharing
• View RSS feeds for journals
• Query GeneRIF interactions, COSMIC mutations, and CNV data for cell lines.
• Does not require a network connection for local databases.
• View and search PubMed in table view.

GeneIndex provides a convenient and portable way to lookup gene symbols while at a seminar, conference, or lab meeting. Genes are linked to common life science websites such as NCBI, COSMIC, KEGG, PubMed, SymAtlas, UCSC genome browser, Pathway Commons, Genatlas, Wikipedia, HUGO, and OMIM. GeneRIF gene interactions can also be queried.

• Keep current on the scientific literature. GeneIndex includes a RSS reader and web browser for browsing popular journals like Nature, Science, and Cell. You can also add your own RSS feeds. PDFs and podcasts can be saved as files that you can view on the device or email as attachments.
• Examine the status of genes in common cell lines. A subset of COSMIC containing cell lines can be queried for mutations. Copy Number Variation (CNV) plots from cell lines profiled by GSK and Sanger are also linked to genes.

More @  https://itunes.apple.com/us/app/geneindex/id319769866?mt=8

Genome Voyager: iPad

Gain first hand experience identifying the genomic basis of disease by analyzing cases with whole genome sequencing data that have been published for research and learning purposes.

• Visualize whole human genome sequencing data including small variations, copy number variations (CNVs), and loss of heterozygosity (LOH) events
• Quickly find variants of interest by filtering variants based on associated genes, functional impact, allele frequency in data sets, and cross-references with various genomic databases.
• Collaborate on variant assessments with other researchers and academics to improve knowledge of both pathogenic and benign variants.
  To use Genome Voyager, users must join Genome Voyager’s community of researchers and academics. Visit http://voyager.completegenomics.com to signup.

More @  https://itunes.apple.com/us/app/genome-voyager/id637353801?mt=8

YeastGenome: iPhone/iPad

Use YeastGenome to quickly find fundamental information about Saccharomyces cerevisae genes and chromosomal features. Search gene names, gene descriptions or browse the database to find information about your favorite gene, as well as more detailed information such as Gene Ontology, mutant phenotype, and protein and genetic interaction data.
YeastGenome contains the latest from the Saccharomyces Genome Database (www.yeastgenome.org) in an on bound app database. As more detailed information is presented the app switches to web services access to SGD, and then for even more details provides complete information via hyperlinks to the appropriate SGD database pages.

Key features:

• Search using gene name or keywords
• Browse by feature type
• Save your favorite features
• Can be used in airplane mode
• Email information about features to collaborators

What's New in Version 1.8.1

• This update is required to provide continued functionality. Some of the data provided by this app accesses the SGD service using a method that is changing in May 2013. This version provides changes to allow access to continue. The on board database of yeast gene information has also been updated to March 2013.

More @  https://itunes.apple.com/us/app/yeastgenome/id520868597?mt=8

SNPdbe: iPhone/iPad

SNPdbe — SNP database of effects, with predictions of computationally annotated functional impacts of SNPs. Database entries represent nsSNPs in dbSNP and 1000 Genomes collection, as well as variants from UniProt and PMD. SAASs come from >2600 organisms; ‘human’ being the most prevalent. The impact of each SAAS on protein function is predicted using the SNAP and SIFT algorithms and augmented with experimentally derived function/structure information and disease associations from PMD, OMIM and UniProt.

More @  https://itunes.apple.com/us/app/snpdbe/id588289719?mt=8

SimGene: iPhone/iPad / Android

SimGene: for iPhone/iPad

SimGene is an iPhone/iPad/iPod touch application designed for molecular biologists, bioinformaticians and medical researchers. The application interfaces with Simbiot, Ensembl, NCBI, Gene Ontology, KEGG Pathways, PubMed, Genomic Variations and many other databases to retrieve up-to-date annotation information for over 30 species, based on gene symbol search. The application provides gene and transcript cross reference information for NCBI, Ensembl, RefSeq and UniProt. SimGene also contains an integrated genome browser with information on genes, transcripts, exons and SNPs.

More @  https://itunes.apple.com/us/app/simgene/id427772349?mt=8

SimGene: for Android

bioinformaticians and medical researchers. The application interfaces with Simbiot,Ensembl, NCBI, Gene Ontology, KEGG Pathways, PubMed, Genomic Variations andmany other databases to retrieve up-to-date annotation information for over 30species, based on gene symbol search. The application provides gene and transcriptcross reference information for NCBI, Ensembl, RefSeq and UniProt. SimGene alsocontains an integrated genome browser with information on genes, transcripts,exons and SNPs.

More @  https://play.google.com/store/apps/details?

TimeTree: iPhone/iPad

TimeTree is a public knowledge-base for information on the evolutionary timescale of life. This application allows easy exploration of the thousands of divergence times among organisms in the scientific literature. A tree-based (hierarchical) system is used to identify all published molecular time estimates bearing on the divergence of two chosen organisms, such as species, compute summary statistics, and present the results. Names of two taxa to be compared are entered in the search window and the results are presented on a set of self-explanatory tabs.

• TimeTree 3.0 was released September 27, 2011 with new data from 1209 studies including 25342 time nodes. We will be adding more data in the future as it comes in from researchers.
• TimeTree is jointly directed by Blair Hedges (Pennsylvania State University) and Sudhir Kumar (Arizona State University). This project has been supported, in part, by grants from the National Science Foundation, National Institutes of Health, NASA Astrobiology Institute, and Science Foundation of Arizona.

More @  https://itunes.apple.com/us/app/timetree/id372842500?mt=8

GeneGroove: iPhone/iPad

GeneGroove is the first application to create a music melody from DTC-Genomics data. If you own 23andMe (Mountain View, CA) personal genomic results, GeneGroove will create for you a unique melody intimately based on your 23andMe genome informations. The music in you.

• After uploading your 23andMe raw data onto your iPhone via iTunes, GeneGroove will analyze your genome informations and generate a unique identifier key. This key, called the GeNumber, will embed the uniqueness of your genome data while keeping your privacy safe, and will be used by GeneGroove to generate your music melody.
• The GeNumber doesn't contain anymore genomic information but it is based on your genome and it is unique, it is yours. It will be used in upcoming Portable Genomics applications to mix and remix music, manipulate sounds and share your art with your friends and family.

More @  https://itunes.apple.com/us/app/genegroove/id492247404?mt=8