Recruitment for Research Associate and Project Assistant positions

Regional Centre for Biotechnology (RCB) is an autonomous academic institution established by the Department of Biotechnology, Govt. of India with regional and global partnerships synergizing with the programmes of UNESCO as a Category II Centre. The primary focus of RCB is to provide world class education, training and conduct innovative research at the interface of multiple disciplines to create high quality human resource in disciplinary and interdisciplinary areas of biotechnology in a globally competitive research milieu.

Research Associate (02 Position)

Consolidated emoluments Rs.22000/- + 30% H.R.A. p.m.

Essential: Ph.D. in Natural Sciences, minimum 60% marks in all qualifying exams and below 35 years of age.

Desirable: Prior experience at the PhD level in Biochemistry, Bioinformatics and Proteomics with a strong motivation for a career in research is highly desirable.

Strong PhD level training with proteins chemistry, protein purification and statistical analysis of proteomics or genomics dataset will be preferred. Either/ both qualifications should be substantiated by published papers.

Inter-Institutional Program for Maternal, Neonatal and Infant Sciences: A translational approach to studying preterm birth.

Principal Investigator: Dr. Dinakar M. Salunke

Applicants may apply along with the requisite documents (attested copies) pertaining to proof of date of birth, academic/professional qualifications, experience (if any), in the prescribed format available on our websites: www.rcb.res.in and www.rcb.ac.in. Applications should be sent to the Registrar, Regional Centre for Biotechnology, 180 Udyog Vihar Phase 1, Gurgaon-122016, Haryana, India, through Registered Post on or before Feb 28, 2014. A soft copy of the application should be sent by email to registrar@rcb.res.in. Incomplete applications or applications received after Feb 28, 2014 will not be entertained.

More at https://www.rcb.res.in/Advt-1._for_websites_PTB-revised.pdf

http://precode-project.eu/jobs-board/#1572451761376-39d75f63-c6fb

Genome Workbench can display sequence data in many ways, including graphical sequence views, various alignment views, phylogenetic tree views, and tabular views of data. It can also align your private data to data in public databases, display your data in the context of public data, and retrieve BLAST results.

Genome Workbench is built on the NCBI C++ ToolKit and uses cross-platform APIs for graphics. It runs on your local machine, and is available for Windows 2000/XP, Linux, MacOS X, and various flavors of Unix.

NCBI Genome Workbench is an integrated application for viewing and analyzing sequence data. Genome Workbench was developed entirely in-house at NCBI and makes use of the NCBI C++ ToolKit. The C++ ToolKit provides a convenient and flexible cross-platform API for managing system internals, database connections, network sockets, and the NCBI data model. In addition, the C++ ToolKit provides the Object Manager, which abstracts handling of sequences and sequence-related objects.

 New Features in Genome Workbench 2.7.15

• Multiple Alignment View: implemented adaptive feature display when zooming in
• Active Objects Inspector replaces Selection Inspector. New View should offer an improved selection context examination. See Using Active Objects Inspector tutorial for more details.
• Binary packages for Linux OpenSUSE 13.1 are now available

Bug Fixes and Improvements in Genome Workbench 2.7.15

• Fixed major issue with OpenGL overlay/scrolling. Could cause crashes or view scrolling irregularities
• Multiple Pane View: fixed crash on loading BLAST results
• Graphical Sequence View: fixed crash on zooming in and out, related to SNP track
• Graphical Sequence View: fixed Go To Position dialog to give better diagnostics in case of a user error
• Graphical Sequence View: PDF export fixed rendering of Markers with commas in the name
• Text View / Flat File: fixed Mac OS rendering issues
• Text View / Flat File: performance optimization, extended capabilities of real-time rendering of molecules to tens of thousands
• File Import: optimization improvement to speed up load of files containing multiple project items
• File Import: remapping stage now shows accession.version and description of molecules, instead of plain GI numbers
• Mac OS: improved tooltips for toolbar buttons
• Phylogenetic Tree Builder Tool: improved diagnostics of errors
• Multiple Alignment View: optimizations to avoid main GUI freezes
• Open Dialog: removed duplicate elements in table of genomes (load Genome)
• PDF export: fixed issue with XREF table errors
• Tree View: fixed issues with showing Force Layout progress on Mac OS
• Tree View: PDF export fixed issues for showing labels of collapsed nodes
• Tree View: added an option to stop layout
• Tree View: broadcasting mechanism fixed not to accumulate selected nodes

Reference:

NCBI news

http://www.ncbi.nlm.nih.gov/tools/gbench/

1 Falcon https://github.com/PacificBiosciences/pb-assembly

2 Canu assembler http://canu.readthedocs.io/en/latest/index.html

3 Miniasm assembler https://github.com/lh3/miniasm

4 PBJelly scaffolding tool https://sourceforge.net/projects/pb-jelly/

5 ARCS scaffolding tool https://github.com/bcgsc/arcs

6 Redundans reduction and scaffolding tool https://github.com/Gabaldonlab/redundans

7 Arrow error correction https://github.com/PacificBiosciences/ GenomicConsensus

8 PILON error correction https://github.com/broadinstitute/pilon/wiki

9 BUSCO single copy gene markers http://busco.ezlab.org/

10 Bandage graph assembly viewer https://rrwick.github.io/Bandage/

11 Gepard dotter http://cube.univie.ac.at/gepard

12 MUMmer aligner and plotter http://mummer.sourceforge.net/

Applications are invited for the posts of one Junior Research Fellow in the DBT funded project entitled “Plant parasitic nematode genome informatics - insilico resource development”. The project is for a period of three years.

Essential qualifications for JRF: First class M. Sc. / M. Tech in Bioinformatics. Knowledge of programming language, pearl, Statistics and database – HTML, CSS, Java script.

Desirable qualifications: Experience in handling next generation sequencing data

Age limit: 35 years maximum (5 year relaxation for SC/ST and women candidates) Emoluments: 16,000 + 30% HRA.

The post is purely temporary in nature and is co-terminus with the project. The appointment would be initially for one year and may be extended further upon satisfactory performance.

Those who are interested in pursuing Ph.D with strong research aptitude are preferred.

Interested candidates may attend the Walk in interview on 25th March 2014 along with the duly filled application forms (format in the following page) with all the relevant documents.

Venue: Division of Nematology, Indian Agricultural Research Institute, New Delhi 110012 (Room No. 306, 3rd floor, LBS building)

Reporting Time: Interested candidates should report strictly between 10.00 to 10.30 AM.

Interview time: 10.30 AM

Short-listed candidates will be called for interview at New Delhi. However, no TA and DA will be paid for attending the interview.

Advertisement:

https://www.iari.res.in/files/JRF_Nema-07032014-20140307-170017.pdf

is a state-funded virtual research center aimed at promoting imaging and informatics research infrastructure in South Dakota. BioSNTR research foci include analysis of large-scale genomics and imaging data, application of novel microscopy technologies to study signaling pathways, and identification of new compounds to manipulate signaling pathways.
Responsibilities: This person will be part of Plant Science team with research focus in bioinformatic and molecular network analyses of high throughput data (transcriptomic, proteomic, metabolomics, miRNA). The individual will be integrated into functional genomic projects encompassing grapevine dormancy and freezing tolerance (Fennell) and regulation of soybean nodulation (Subramanian). The successful candidate will perform computational analysis of high throughput, next-generation sequence data and possess the ability to use bioinformatics analytical tools on HPC clusters.

Required Qualifications:
• Ph.D. in plant computational biology or bioinformatics.
• Experience in a high performance computing environment.
• Perl, Python and Java programming experience
• Data management and database development experience

Desired Qualifications:
• Parallel computing experience
• Experience working in a multidisciplinary environment

Contact Information
South Dakota State University
Plant Science
Anne Fennell
anne.fennell@sdstate.edu
Tel. Number: 605-688-6373
http://www.biosntr.org

Mandatory requirements
Knowledge of #Python,#PERL,#R (one or more) and shell environment (#linux )
Knowledge about database - #mysql, #oracle, #mongodb (one or more)
Past industry experience >= 2 years or equivalent

Other skill sets
Knowledge of #nextflow and/or #snakemake
Basic knowledge of bioinformatics/genomics

Send your applications to careers@medgenome.com

In our day to day research activity, we need to securely copy our data from several to local computer and visa-versa. I am jotting down some of the commonly used SCP command for your future help. Hope you all will like it

What is Secure Copy?

scp allows files to be copied to, from, or between different hosts. It uses ssh for data transfer and provides the same authentication and same level of security as ssh.

Examples

Copy the file "gene.txt" from a remote host to the local host

    $ scp your_username@remotehost.edu:gene.txt /some/local/directory

Copy the file "foobar.txt" from the local host to a remote host

    $ scp gene.txt your_username@remotehost.edu:/some/remote/directory

Copy the directory "chromosome" from the local host to a remote host's directory "bar"

    $ scp -r chromosome your_username@remotehost.edu:/some/remote/directory/bar

Copy the file "gene.txt" from remote host "rh1.edu" to remote host "rh2.edu"

    $ scp your_username@rh1.edu:/some/remote/directory/gene.txt \
    your_username@rh2.edu:/some/remote/directory/

Copying the files "gene.txt" and "cancer.txt" from the local host to your home directory on the remote host

    $ scp gene.txt cancer.txt your_username@remotehost.edu:~

Copy the file "gene.txt" from the local host to a remote host using port 2264

    $ scp -P 2264 gene.txt your_username@remotehost.edu:/some/remote/directory

Copy multiple files from the remote host to your current directory on the local host

    $ scp your_username@remotehost.edu:/some/remote/directory/\{a,b,c\} .

    $ scp your_username@remotehost.edu:~/\{gene.txt,cancer.txt\} .

scp Performance

By default scp uses the Triple-DES cipher to encrypt the data being sent. Using the Blowfish cipher has been shown to increase speed. This can be done by using option -c blowfish in the command line.

    $ scp -c blowfish some_file your_username@remotehost.edu:~

It is often suggested that the -C option for compression should also be used to increase speed. The effect of compression, however, will only significantly increase speed if your connection is very slow. Otherwise it may just be adding extra burden to the CPU. An example of using blowfish and compression:

    $ scp -c blowfish -C local_file your_username@remotehost.edu:~

Adapter sequences:
Optimal enzymes for amplifying sequencing libraries.
Quail, M. a et al. Nat. Methods 9, 10-1 (2012).

GAGE:
GAGE: A critical evaluation of genome assemblies and assembly algorithms.
Salzberg, S. L. et al. Genome Res. 22, 557-67 (2012).

KMC:
Disk-based k-mer counting on a PC.
Deorowicz, S., Debudaj-Grabysz, A. & Grabowski, S. BMC Bioinformatics 14, 160 (2013).

Kraken:
Kraken: ultrafast metagenomic sequence classification using exact alignments.
Wood, D. E. & Salzberg, S. L. Genome Biol. 15, R46 (2014).

MUMmer:
Versatile and open software for comparing large genomes.
Kurtz, S. et al. Genome Biol. 5, R12 (2004).

R:
R: A language and environment for statistical computing.
R Core Team (2013). R Foundation for Statistical Computing, Vienna, Austria. URL http://www.R-project.org/.

RATT:
RATT: Rapid Annotation Transfer Tool.
Otto, T. D., Dillon, G. P., Degrave, W. S. & Berriman, M. Nucleic Acids Res. 39, e57 (2011).

SAMtools:
The Sequence Alignment/Map format and SAMtools.
Li, H. et al. Bioinformatics 25, 2078-9 (2009).

Trimmomatic:
Trimmomatic: A flexible trimmer for Illumina Sequence Data.
Bolger, A. M., Lohse, M. & Usadel, B. Bioinformatics 1-7 (2014).