Address of the bookmark: http://schizophreniaforum.org/new/detail.asp?id=1953

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

http://cancerwebpa.jefferson.edu/iSeqQC/

https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-020-3399-8

Address of the bookmark: https://github.com/gkumar09/iSeqQC

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

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

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

Why Normalize RNA-Seq Data?

Normalization is a crucial step in RNA-Seq analysis for the following reasons:

• Sequencing depth: Different RNA-Seq experiments produce varying numbers of reads, making direct comparisons between samples misleading.

• Gene length: Longer genes inherently generate more reads, irrespective of their actual expression level.

• Bias reduction: Normalization mitigates technical biases, enabling meaningful biological interpretation.

TPM (Transcripts Per Million)

TPM measures the proportion of reads mapped to a transcript, normalized by transcript length and sequencing depth. It is calculated as:

Key Features:

1. Proportionality: TPM values sum to 1,000,000 across all transcripts in a sample, making it easier to compare between samples.

2. Intuitive interpretation: TPM values directly represent the abundance of transcripts in a sample.

3. Preferred for comparisons: TPM facilitates between-sample comparisons better than FPKM.

FPKM (Fragments Per Kilobase Million)

FPKM normalizes read counts by transcript length and sequencing depth, but without enforcing proportionality like TPM. It is defined as:

Key Features:

1. Historical significance: FPKM was one of the first normalization methods used for RNA-Seq.

2. Single-end vs. paired-end: In paired-end sequencing, FPKM becomes RPKM (Reads Per Kilobase Million).

3. Limited utility: FPKM values are not as robust as TPM for cross-sample comparisons due to lack of proportionality.

CPM (Counts Per Million)

CPM normalizes raw read counts by sequencing depth, without considering gene length. It is expressed as:

Key Features:

1. Simplicity: CPM is straightforward and computationally less intensive.

2. Application: Suitable for non-length-dependent analyses, such as comparing total expression levels or differential expression analysis.

3. Gene length agnostic: CPM does not correct for gene length, making it less ideal for measuring expression levels.

When to Use Each Method

• TPM: Best for comparing expression levels between samples, especially when transcript length and sequencing depth vary.

• FPKM: Useful for historical consistency but generally replaced by TPM.

• CPM: Ideal for differential expression analysis when gene length normalization is unnecessary.

Conclusion

Choosing the right normalization method depends on the specific objectives of your RNA-Seq analysis. TPM’s proportionality and robustness make it the preferred choice for most applications, while CPM serves well for differential expression studies. Although FPKM paved the way for RNA-Seq normalization, it has largely been supplanted by TPM in modern workflows. Understanding these methods and their nuances ensures accurate and meaningful interpretations of RNA-Seq data.

References:

1. Li, B., & Dewey, C. N. (2011). RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinformatics.

2. Trapnell, C., et al. (2010). Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation. Nature Biotechnology.

3. Law, C. W., et al. (2014). voom: precision weights unlock linear model analysis tools for RNA-seq read counts. Genome Biology.

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

Online version and downloadable software package for offline use (source code in PERL) freely available at http://bat.ina.certh.gr/tools/circoletto/

Contact:ndarz@certh.gr

Address of the bookmark: http://tools.bat.infspire.org/circoletto/

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