This collection highlights important statistical issues that biologists should be aware of and provides practical advice to help them improve the rigor of their work.

Nature Methods' Points of Significance column on statistics explains many key statistical and experimental design concepts. Other resources include an online plotting tool and links to statistics guides from other publishers.

Address of the bookmark: http://www.nature.com/collections/qghhqm

Paper at https://gigascience.biomedcentral.com/articles/10.1186/s13742-015-0076-3

Address of the bookmark: https://github.com/warrenlr/LINKS/

ESSENTIAL QUALIFICATIONS:
We are looking for a motivated candidate with keen interest in bioinformatics and microbial genome evolution. The candidate must have a Master’s Degree in Bioinformatics, Computational Biology, Computer Science, Microbiology, Biology or a related field with good academic record.

DESIRABLE QUALIFICATIONS
Hands on research experience on handling next generation sequencing data and phylogenetic reconstruction methods. Excellent programming skills (Perl/Python/Java/Php) and experience in working on Unix/Linux platform is preferred. Furthermore; good knowledge is required in statistics (R/Matlab) and the application of bioinformatics analysis tools.

AGE:
Below 28 years as on 15th November, 2016.

EMOLUMENTS:
Rs. 25,000 + 20% HRA for NET/GATE qualified and Post Graduate in Professional Degree course qualified candidates and
Rs. 12,000/- + 20% HRA for others.

DURATION:
Initial appointment will be given for one year and further extension will be based on the performance till termination of the project.
Only those fulfilling the above criteria need apply and will be called for interview. In the event of more than 10 candidates being short-listed by screening the applications, a written test will be conducted before the selection interview and only those who are successful in the written test will be interviewed. No TA/ DA will be given for appearing in the interview.

Suitably qualified candidates may send applications in the prescribed format (Download here) with a photograph, a copy of full resume indicating the percentage of Marks obtained and attested photocopies of credentials & experience to reach the undersigned on or before 15th November, 2016. Envelopes must be superscripted with abbreviated title of the project, advertisement number and job title. Selection to the position will not entitle the candidate to any future positions at RGCB (permanent or otherwise). As with all project positions at RGCB, the position will be co terminus with end of the project.

Please bookmarks your favourate biostatistics books in commend sectons ...

Address of the bookmark: http://www.cos.ufrj.br/~bioestatistica/livros/Introduction%20to%20Biostatistics.pdf

Research Assistant Bioinformatics recruitment in National Institute Of Cancer Prevention & Research (ICMR) on Contract basis
Project entitled: “Next generation EGFR inhibitor identification using ligand based QSAR technique”

Essential: M.Sc. in Bioinformatics or related field. Desirable: Experience in QSAR and structure based drug designing.
Age: 28 years
No.of Post: 1

Pay Scale : Rs.27000

Application format is attached and should be sent by post to Dr. Subhash M Agarwal, Scientist D, Division of Bioinformatics, National Institute of Cancer Prevention & Research (ICMR), Plot No. I-7, Sector-39, Noida 201301 (U.P).

More at http://www.icmr.nic.in/icmrnews/NICPR_Advertisement%20for%20RA.pdf

Run Maq Now

Follow these steps to try Maq. All you need is a reference sequence file in the FASTA format.

1. Prepare a reference sequence (ref.fasta). Better a bacterial genome.
2. Download maq, maq-data and maqview at the download page.
3. Copy maq, maq.pl and maq_eval.pl to the $PATH or to the same directory.
4. Simulate diploid reference and read sequences, map reads, call variants and evaluate the results in one go:

   maq.pl demo ref.fasta calib-30.dat
   

   where calib-30.dat is contained in maq-data.
5. View the alignment:

   cd maqdemo/easyrun;
   maqindex -i -c consensus.cns all.map;
   maqview -c consensus.cns all.map

Even for advanced maq users, running `maq.pl demo' is recommended. You may find something helpful.

Address of the bookmark: http://maq.sourceforge.net

https://github.com/aalokaily/Hierarchical-Genome-Assembly-HGA

Address of the bookmark: https://github.com/aalokaily/Hierarchical-Genome-Assembly-HGA

Address of the bookmark: http://augustus.gobics.de/binaries/scripts/

Address of the bookmark: http://journal.embnet.org/index.php/embnetjournal/article/view/208

Address of the bookmark: https://github.com/alastair-droop/fqtools