As with most programs that run on UNIX, the text output is in some specific format. If the program is popular enough, there will be one or more parsers written for that format – these are just utilities written to help you retrieve whatever information you are interested in from the output.

Let’s conclude this tutorial by converting the BLAST output in out.txt into a spreadsheet format, using a Python script. 

First, we need to get the script. We’ll do that using the ‘git’ program:

git clone https://github.com/ngs-docs/ngs-scripts.git /root/ngs-scripts

We’ll discuss ‘git’ more later; for now, just think of it as a way to get ahold of a particular set of files. In this case, we’ve placed the files in /root/ngs-scripts/, and you’re looking to run the script blast/blast-to-csv.py using Python:

python /root/ngs-scripts/blast/blast-to-csv.py out.txt

This outputs a spread-sheet like list of names and e-values. To save this to a file, do:

python /root/ngs-scripts/blast/blast-to-csv.py out.txt > ~out.csv

If you have Excel installed, try double clicking on it.

Project Fellow – One Post

Duration: Three Years

Fellowship : Rs.14, 000/- per month + HRA

Walk-in-interview: 16th Sept, 2013 at 10.00 am

Venue : Department of Bioinformatics, Alagappa University

Eligible candidates can attend walk in interview for the post of Project Fellow in UGC supported project entitled “Shape and chemical feature based 3D- Pharmacophore Model generation, Virtual Screening and MESP studies to identify Potential Leads for Antifungal Azoles”

Interested candidates may apply to Dr. Sanjeev Kumar Singh, Principal Investigator, Department of Bioinformatics, Karaikudi with their Curriculum Vitae along with the copies of the certificates in proof of their educational qualification and experience at skysanjeev@gmail.com

Qualification:

PG Degree in Bioinformatics / Chemistry/ Molecular Biology/ Biotechnology / Biophysics / Biochemistry / Life Sciences/ Pharmacy with minimum of 55% marks in the PG examinations

Desirable:

Research experience in Molecular modeling and CADD will be given preference. UGC-NET/ CSIR-JRF qualified candidates will get preference.

The posts are purely on temporary basis. No TA/DA will be paid for attending the interview.

Advertisement: http://www.alagappauniversity.ac.in/files/news_files/new%20advt-UGC-16sept,13.doc

WALK-IN-INTERVIEW

A walk-in-Interview is proposed to be held at National Bureau of Animal Genetic Resources, Karnal (Haryana)-132001 at 11:30 AM on 18.12.2013 to select One RA and One SRF as per details given below:

1. One post of Research Associate under DBT sponsored Support under BIPP for the “SanGenix: A comprehensive Next Generation Sequence (NGS) data analysis solution” as Grants in AID. Thepost duration is Upto 31st March 2015 or earlier.

2. One post of Senior Research Fellow under NAIP (Component-4) Bioprospecting of genes and allele mining for abiotic stress tolerance. The post duration is Upto 31st March 2014 or earlier

Essential Qualifications: Ph.D. in Bioinformatics/ Computer Application or
First Class Masters degree in Bioinformatics/ Computer Application with two years experience as evidenced by Publications.

Desirable: Experience in the field of handling Next generation Sequencing Data.

Emolument: Rs. 22,000/- per month + HRA as per admissibility

Age Limit:

40 years for Men
45 years for women as on date of interview

Research Associate: ONE

Duration of engagement: Upto

31st March 2015 or earlier & Coterminus with the project

Responsibilities: To help the PI for Beta testing and development of the SanGenix Tool for NGS data.

Essential Qualifications: First Class Masters’ degree in Bioinformatics/Biotechnology.

Desirable: Experience in the field of Biotechnology/ Bioinformatics

Emoluments:

Rs. 16,000/- per month + HRA as per admissibility.
Senior Research Fellow: ONE
Duration of engagement: Upto 31st March 2014 or earlier & Coterminus with the project

Age Limit

35 years for men
40 years for women as on date of interview

Note: Relaxation in age will be admissible for SC/ST & OBC candidates as per Govt. of India /ICAR norms

1. The applicants must bring with them original documents and brief of research work done during post graduation along with a set of photocopy and latest two passport size photographs.
2. A panel of selected candidates will also be made which may be utilized for filling of positions of shorter durations in future if demand arises.
3. Experience certificate in original, if any 4. The above positions are purely on temporary basis and are co-terminus with the project. No TA/DA will be paid to attend the interview.
5. Any other clarifications can be had on the date of interview.
6. The Director’s decision will be final and binding on all respects.

Advertisement: http://210.212.93.85/rasrfadvertise.pdf

Key Features of BLAST:
1. Sequence Comparison: BLAST searches for local alignments between the query sequence and sequences in a database. It identifies regions of similarity, which can help infer functional and evolutionary relationships.

2. Speed and Efficiency: BLAST uses heuristic algorithms, making it faster than exhaustive search methods, suitable for large-scale database searches.

3. Versatility: There are several versions of BLAST for different types of sequence comparisons:
- blastn: Compares a nucleotide query sequence against a nucleotide sequence database.
- blastp: Compares a protein query sequence against a protein sequence database.
- blastx: Compares a nucleotide query sequence translated in all reading frames against a protein sequence database.
- tblastn: Compares a protein query sequence against a nucleotide sequence database translated in all reading frames.
- tblastx: Compares the six-frame translations of a nucleotide query sequence against the six-frame translations of a nucleotide sequence database.

4. Scoring and E-value: BLAST results are scored based on the quality and length of the alignments. The E-value (expect value) indicates the number of alignments one can expect to find by chance, with lower E-values representing more significant matches.

5. Output Formats: BLAST provides results in various formats, including plain text, HTML, XML, and JSON, making it adaptable for different types of analyses and integrations with other tools.

Applications of BLAST:
- Genomic Research: Identifying genes, understanding genetic diversity, and mapping genome sequences.
- Protein Function Prediction: Inferring the function of unknown proteins by comparing them to known protein sequences.
- Evolutionary Studies: Exploring evolutionary relationships between organisms by comparing their genetic material.
- Medical Research: Identifying pathogens, understanding disease mechanisms, and developing treatments by comparing sequences of interest.

Overall, BLAST is an essential tool in bioinformatics, offering a reliable and efficient way to analyze and interpret biological sequence data.

More at http://www.mathivananlab.org/index.html

http://scholar.google.com/citations?user=U6PyEdYAAAAJ&hl=en

RMBlast supports RepeatMasker searches by adding a few necessary features to the stock NCBI blastn program. These include:

• Support for custom matrices ( without KA-Statistics ).
• Support for cross_match-like complexity adjusted scoring. Cross_match is Phil Green's seeded smith-waterman search algorithm.
• Support for cross_match-like masklevel filtering.

https://anaconda.org/bioconda/rmblast

Address of the bookmark: http://www.repeatmasker.org/RMBlast.html

More at http://www.ircc.iitb.ac.in/IRCC-Webpage/rnd/RecruitmentGenerateCircular.jsp?srno=2013086

Address of the bookmark: https://kablammo.wasmuthlab.org/