Address of the bookmark: https://github.com/broadinstitute/VariantBam

Name of the Project : Network Project on Agricultural Bioinformatics Number of positions One
Qualifications : Ph.D Degree in Bioinformatics/Biotechnology/ Biochemistry/Genetics & Breeding/Life Sciences OR Master’s Degree in relevant subject with at least 2 years research experience. Desirable : Working experience in Molecular Biology/Genomics/Bioinformatics, specifically, sequence data analysis using software’s proficiently

Emoluments : Masters Degree Holders Rs. 38,000/- per month Doctoral Degree Holders Rs. 40,000/- per month

Emoluments : Rs.25000/- per month for 1st and 2nd year and Rs. 28000/- per month for 3rd year
Age Limit : Upper age limit is 35 years for men and 40 years for women on the date of interview. Age relaxation for SC/ST and OBC candidates as per rules

More at http://www.cirb.res.in/attachments/195_walk-in-interview%20for%20contractual%20positions%20of%20RA%20and%20SRF%20%28On%20Dated%2011.8.2015%29.pdf

• Binaries for Linux/macOS
• From sources for Linux/macOS
• From sources for Windows

Address of the bookmark: https://github.com/imgag/ngs-bits

Interested candidates may appear before the interview board on 23 February, 2015 at the Office of the Head, Department of Molecular Biology & Biotechnology, Tezpur University with original documents and photocopies of marks sheets, certificates, testimonials, caste certificate (if applicable), experience certificate and a copy of curriculum vitae (CV) duly signed by the candidate.

Position: One (01) Research Associate.

Educational Qualification: Candidates having Ph.D. degree or submitted thesis in any topic of Life Science Areas (Zoology, Botany, Microbiology, Biotechnology etc.) along with knowledge of gene and protein sequence analysis may apply.

Remuneration: Rs. 22,000/- (Rupees twenty two thousand) only + 10% HRA as admissible per month for the first year and Rs. 23,000/- (Rupees twenty three thousand) only + 10% HRA as admissible per month for the second year.

Age: Candidate preferably below the age of 40 years who have obtained a doctorate (Ph.D.) degree from a recognized University.

Upper age limit may be relaxed up to 5 years in the case of candidates belonging SC/ST/OBC/Women and physically challenged.

Position: One (01) Project Assistant.

Educational Qualification: B.Sc./B.Tech./B.E./B.Pharma in any branch with minimum 55% mark in the qualifying examinations and minimum 50 % mark in 10th and 10+2 Science examinations.

Remuneration: Rs. 8,000/- (Rupees eight thousand) only per month (consolidated). Age: Candidate should not be more than 28 years of age on the date of interview. Upper age limit may be relaxed up to 5 years in the case of candidate belonging to SC/ST/OBC/Women/Physically Challenged.

Duration: One year or till completion of the project, whichever is earlier. N.B. No TA/DA will be paid to the candidates for attending the interview.

For further information contact – Dr. Suvendra Kumar Ray, Associate Professor Email: suven@tezu.ernet.in Department of Molecular Biology and Biotechnology Tezpur University Sd/- Dean, Research & Development Tezpur University

Advertisement: http://www.tezu.ernet.in/ProjectWalkin/Advt-SKR2-5342-A.pdf

Link @ http://www.bioinf.uni-freiburg.de/

Title of the Project
Research Associate
(One position)
DBTs Biotechnology/Bioinformatics training centre
PI Dr. Ashok Varma

Duration of the Project Six Months from the date of appointment, can be extended further for six month.

Date & Time: 17th February, 2015 at 10.00 a.m.

Venue: Meeting Room, 3rd floor, Khanolkar Shodhika, ACTREC

Essential Qualifications and Experience:

Ph.D. Degree in Basic Sciences from recognized University. Research experience in Bioinformatics or on gene cloning, protein purification, and crystallization.

*M.Sc. degree obtained after a one year course will not be considered.

Selected candidate will have to join at the earliest.

Consolidated Salary: Rs.28,600/- p.m. {Rs.22,000/- + 30% HRA}

The work progress of the candidate will be monitored and extension after 6 months will depend on satisfactory progress of the work.

Candidates fulfilling these requirements should pre-register by sending their application in the prescribed format with recent CV and contact details of 2 referees by e-mail to ‘program.office@actrec.gov.in’ latest by 17.00 hrs on 12-02-2015.
The interviews would be held on 17th February, 2015 and will be only for the pre-registered candidates. Candidates should report between 09.30 to 10.00 a.m. in Steno Pool, 3rd floor, Khanolkar Shodhika, ACTREC, Kharghar, Navi Mumbai.
No T.A./D.A. will be admissible for attending the interview.

At the time of Interview the candidate should bring original certificates along with CV with contact details of 2 referees and submit the photocopies (attested) of the certificates, with a recent passport size photograph.

All correspondence should be strictly made only to ‘program.office@actrec.gov.in’ as indicated.

Advertisement: www.actrec.gov.in/data%20files/2015/AV-RA-DBT-28-1-15.docx

Who you are
You’re someone who wants to influence your own development. You’re looking for a company where you have the opportunity to pursue your interests across functions and geographies. Where a job title is not considered the final definition of who you are, but the starting point.

Qualifications:
Major: Bioinformatcis or biology major who is interested and wants to learn Biocomputing, At least 2 years of college.
Basic knowledge of LINUX and programming, e.g., perl, python, XML.

More at http://www.roche.com/careers/jobs/jobsearch/job.htm?id=E-00437679&locale=en&title=Summer%20Intern%20-%20Research%20Bioinformatics

version 1.0.0 - updates several descriptions and tests. To achieve v0.9.4, one can visit https://github.com/zhyqin/SEASTAR-0.9.4 for download.

Address of the bookmark: https://github.com/Xinglab/SEASTAR

Name of the Scheme : Distributed Information Sub Centre – DISC

Qualifications : M.Sc/ B Tech in Bioinformatics with NET/GATE or M Tech in Bioinformatics

Number of posts : One

Emoluments : Rs. 25,000/-

Upper age limit : 35 years for Men & 40 years for Women as on date of Interview
How to apply

Date of Interview : 12-03-2015 at 10.00 AM. All relevant certificates (in original) and bio data, No objection certificate in case he/she is employed elsewhere and experience certificate in original (if any) need to be produced at the time of interview.

More at http://spices.res.in/index.php?option=com_content&view=article&id=263

This blog provides a comprehensive step-by-step guide to detect piRNAs using bioinformatics tools and workflows.

Step 1: Prepare Your Data

1. Obtain RNA Sequencing Data
   Acquire raw small RNA-seq data in FASTQ format. Datasets can be sourced from repositories like NCBI SRA, EMBL-EBI, or specific small RNA sequencing projects.

2. Quality Control (QC)
   Use FastQC to assess the quality of raw reads:

   fastqc reads.fastq

   Evaluate the per-base quality, adapter content, and overrepresented sequences.

3. Trimming and Adapter Removal
   Use tools like Cutadapt or Trim Galore! to remove adapters and low-quality bases:

   cutadapt -a TGGAATTCTCGGGTGCCAAGG -o trimmed_reads.fastq reads.fastq

   Ensure the remaining reads are of high quality for downstream analysis.

Step 2: Map Reads to the Genome

Mapping reads to the reference genome is crucial for identifying piRNA loci.

1. Reference Genome Preparation
   Download the genome assembly of your organism from databases like Ensembl, UCSC Genome Browser, or NCBI.

2. Align Reads
   Use Bowtie or STAR for small RNA alignment:

   bowtie -v 1 -k 1 --best genome_index trimmed_reads.fastq -S aligned_reads.sam
   • -v 1: Allows one mismatch.
   • -k 1: Reports the best alignment.

3. Convert SAM to BAM
   Convert and sort alignments using SAMtools:

   samtools view -Sb aligned_reads.sam | samtools sort -o sorted_reads.bam

Step 3: Identify Small RNAs

piRNAs are characterized by their size (24–32 nt) and strand bias.

1. Extract Reads by Size
   Use tools like BEDtools or custom scripts to filter reads between 24 and 32 nt:

   bedtools bamtofastq -i sorted_reads.bam -fq all_reads.fastq seqkit seq -m 24 -M 32 all_reads.fastq > piRNA_size_reads.fastq

2. Check for Sequence Bias
   piRNAs often have a strong bias for a uridine at the 5’ end (1U bias). Use tools like WebLogo to visualize sequence motifs.

Step 4: Detect Ping-Pong Signature

The ping-pong amplification loop is a hallmark of piRNA biogenesis, characterized by a 10 nt overlap between piRNAs on opposite strands.

1. Generate Overlap Statistics
   Use the piPipes tool or custom scripts to calculate overlap:

   python ping_pong_overlap.py sorted_reads.bam

2. Visualize Overlap Distribution
   Plot the distribution of overlaps to confirm the presence of the 10 nt ping-pong signature.

Step 5: Annotate piRNA Clusters

piRNAs are often generated from genomic clusters.

1. Cluster Identification
   Use tools like proTRAC or PIRANHA to identify piRNA-producing clusters:

   proTRAC.pl -s sorted_reads.bam -g genome.fa -o clusters

2. Annotate Genomic Regions
   Annotate the identified clusters using gene annotation files (GTF/GFF). Tools like BEDtools intersect can help associate piRNA clusters with genes or transposable elements:

   bedtools intersect -a clusters.bed -b genome_annotation.gtf > annotated_clusters.bed

Step 6: Functional Analysis

Functional analysis of piRNAs can uncover their targets and regulatory roles.

1. Predict piRNA Targets
   Use tools like IntaRNA or RNAhybrid to predict interactions between piRNAs and potential target mRNAs:

   RNAhybrid -t target_transcripts.fa -q piRNAs.fa > piRNA_targets.txt

2. Enrichment Analysis
   Perform GO or KEGG enrichment analysis of target genes using tools like g:Profiler or DAVID.

Step 7: Validation and Visualization

1. Validate piRNA Candidates
   Cross-check the identified piRNAs against known piRNA databases, such as piRBase or piRNAdb.

2. Visualize Results

   • Use IGV (Integrative Genomics Viewer) to visualize piRNA alignment and clusters on the genome.
   • Generate heatmaps or circos plots to present piRNA distributions.

Step 8: Share and Publish Findings

1. Archive Data
   Submit sequencing data to public repositories like SRA or GEO with metadata specifying piRNA-related experiments.

2. Publish Results
   Share findings in journals or conferences, emphasizing novel piRNA candidates, target genes, or regulatory mechanisms.

Conclusion

Detecting piRNAs involves a combination of computational and analytical methods to identify these unique small RNAs and their roles in gene regulation and transposable element suppression. By following this step-by-step guide, you can confidently navigate the complexities of piRNA detection and contribute to the growing understanding of their biological significance.