Post: Junior Research Fellow (1 Position)

Duration: Three years

Qualification: First class in M.Sc/M.tech in Bioinformatics/Life Sciences/Biophysics/ Biostatistics/Bioengineering. Experience in Database development, NGS data analysis, Systems Biology and Structural Bioinformatics is desired. Preference will be given to the candidates with good computer programming skills in C, C++, R, Perl, PHP, Unix Scripting etc.

Selected candidates will be paid fellowship as per existing DST norms.

How to apply:

Candidates are requested to apply through one of the two modes given below
1. Online application – Click here to submit the online application https://docs.google.com/forms/d/16h2GLnQ-Ny-tLtlgfY3Bx3sCjeHJE30cfhJaDqW_uRs/viewform?c=0&w=1
2. Application forms can be downloaded from here.https://docs.google.com/file/d/0BwwJEudQStxFWXdNWXl4NWtDaWc/edit
Filled in application form should be sent by post to Dr. D. Bharanidharan, Department of Bioinformatics, Aravind Medical Research Foundation No 1, Anna Nagar Madurai – 625 020,

Candidates should apply by online or submit their applications by post on or before 15th June, 2015. Only Short listed candidates will be called for an interview. No TA/DA will be paid.

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.

#Find all occurrences of a pattern in a string.
#Given: Strings Pattern and Genome.
#Return: All starting positions in Genome where Pattern appears as a substring. Use 0-based indexing.

use strict;
use warnings;

my $string="GATATATGCATATACTT";
my $subStr="ATAT";
my $kmer=length($subStr);

kmerMatch ($string, $subStr, $kmer);

sub kmerMatch { #Check the exact matching kmers with sliding window
my ($string, $myStr, $kmer)=@_;
for (my $aa=0; $aa<=(length($string)-$kmer); $aa++) {
    my $myWin=substr  $string, $aa,$kmer;
    if ($myWin eq $myStr) {
        #print "$myWin eq $myStr\n";
        print $aa;
    }
}
}

Address of the bookmark: http://www.dkfz.de/en/applied-bioinformatics/telomerehunter/telomerehunter.html

• Expansion of Protists and Fungi with hundreds of annotated genomes
• Variation data for bread wheat, rice, Aedes aegypti, and Ixodes scapularis
• Whole genome alignments for O. longistaminata and T. cacao
• Non-coding RNA gene models in Bacteria
• New assembly of tomato (version 2.50)
• Full support for UCSC Track Hub format for hosting your own data in Ensembl

More at http://www.ensembl.info/blog/2015/06/16/ensembl-genomes-release-27-is-out/

Availability: RAMI is licensed under GNU GPL and can be run or downloaded from http://www.acgt.se/online.html.

Address of the bookmark: https://academic.oup.com/bioinformatics/article-lookup/doi/10.1093/bioinformatics/btp051

Minimum qualification: MSc in any branch of life sciences

Applications are invited for the position of a Research Assistant in the Centre for Human Genetics, Bangalore.

The project involves identification of mutations in MPS (mucopolysaccharidosis) patients, and study of their predicted effects to understand how the mutations lead to disease.

Techniques used will be genomic DNA isolation, PCR, DNA sequencing and sequence analysis. Computational tools would also be used to analyse and interpret data.

Candidates may be assigned work in the ongoing project or in new ones.

The candidate who is selected and joins would acquire hands-on experience in research and the capability to conduct insightful research.

Candidates applying for the position should have an MSc in any branch of life sciences. Those with research experience in cell and molecular biology, and high NET/ GATE score would be preferred.

The successful applicant is expected to stay for at least one and a half years.

Please apply with CV to Sudha Srinivasan (sudha@ibab.ac.in), stating where you saw this ad.

Address of the bookmark: https://github.com/rhysf/Synima

Address of the bookmark: http://genome.cs.nthu.edu.tw/Multi-CAR/

The next-generation sequencing included whole genome sequencing(WGS), transcriptome sequencing (whole cDNA sequencing, RNA-seq), digital gene expression sequencing (Tag-Seq), ChIP-Seq, and so on. And there are many sequencing platform to generate sequece, as well know Sanger/ABi(the frist generation), Solexa/illumina, SOLiD/ABi, 454/Roche. But thier sequence format is different, also they have different error type. High quality data is very important for further analysis or data mining. There are many pipeline for raw sequence quality analysis and control with few of process for reporting reads quality statistical details, trimming, filtering, and error correction. Please bookmarks them for the benefits of bioinformatics community.

https://code.google.com/p/biowiki/

https://code.google.com/p/ngs-pipeline/source/browse/#svn%2Ftrunk

NGSand Perl scripts https://code.google.com/hosting/search?q=NGS+perl&projectsearch=Search+projects

NGS and Python scripts https://code.google.com/hosting/search?q=NGS+Python&projectsearch=Search+projects

Address of the bookmark: https://code.google.com/hosting/search?q=bioinformatics&sa=Search