Address of the bookmark: https://github.com/sc932/ALE

Vacancies:
Research Associate-02
Age Limits:
Candidates age limit should be not more than 40 years as on date of interview.
Qualification:
Candidates should possess Ph.D in Bioinformatics/Agricultural Statistics/Statistics/Computer Science/Computer Application or equivalent.
Selection Process:
Selection will be based on interview.
How to Apply:
Eligible candidates may attend for interview along with application in prescribed format, recent passport size photograph pasted on the application form, bio-data, original certificates and self attested copies of relevant documents, all experience certificates, testimonials etc, held at Indian Agricultural Statistics Research Institute, Pusa, New Delhi on 18-04-2015 at 10:30 AM.
Last Date:
18-04-2015

To find repeats in a genome from 2 to 9 length using a Perl script, you can use the RepeatMasker tool with the "--length" option[0]. Here's a step-by-step guide:

Overview of SLiM and msprime

SLiM: Forward Genetic Simulator

SLiM is a free, open-source tool designed for forward genetic simulations. It allows researchers to model complex evolutionary scenarios, including selection, recombination, and demographic events, making it particularly useful for studying adaptation and selection in populations.

Key Features of SLiM:

• Simulates population evolution forward in time

• Supports custom evolutionary models using an embedded scripting language

• Allows modeling of spatial and ecological dynamics

• Provides high flexibility and extensibility for user-defined scenarios

• Available on GitHub as an open-source project

msprime: Ancestry and Mutation Simulator

msprime is an efficient, open-source tool that simulates ancestry and mutations using a coalescent framework. It is known for its high-speed performance and low memory requirements, making it a popular choice for large-scale genomic simulations.

Key Features of msprime:

• Implements coalescent simulations for ancestry modeling

• Efficiently simulates large population histories

• Supports the addition of mutations to genealogies

• Developed using an open-source community model

• Often faster and more memory-efficient than alternative simulators

Using SLiM and msprime with slendr

Both SLiM and msprime can be integrated with slendr, a framework that facilitates structured population genetic simulations. This integration allows for seamless comparison of simulation outputs.

How They Work Together:

• SLiM and msprime simulations can be analyzed within slendr.

• The ts_read() function in slendr enables loading and comparing tree sequence outputs from both simulators.

• This integration allows researchers to validate simulation results and gain deeper insights into evolutionary processes.

Performance Considerations

While SLiM offers powerful forward simulations with extensive customization, msprime is often preferred for its speed and memory efficiency when simulating ancestry and mutations. The choice between the two depends on the research goals:

• For detailed evolutionary modeling with selection and recombination: Use SLiM.

• For large-scale coalescent simulations with mutations: Use msprime.

• For comparing different simulation models and their outputs: Use slendr to integrate SLiM and msprime results.

Conclusion

SLiM and msprime are valuable tools for genome simulation, each serving distinct but complementary purposes in population genetics research. By leveraging the strengths of both simulators with slendr, researchers can conduct robust and efficient evolutionary simulations, enhancing our understanding of genetic diversity and adaptation.

For more information, check out the official GitHub repositories for SLiM and msprime, and explore the slendr framework for streamlined simulation workflow

National Institute of Biologicals (NIB), Noida invites applications to recruit on vacant posts of Scientist, Training Officer, Administrative Assistant, Stenographer, Junior Engineer, Computer Operator etc. Applications against these Government Jobs can be submitted on or before 01 July 2015.

NIB Vacancy 2015 Details
1. Scientist Grade III – 06
Qualification: PG degree in the concern field.
Age Limit: 35 Years

2. Junior Scientist – 07
Qualification: M.Sc. in Microbiology / Clinical Microbiology / Biotechnology/ Bioinformatics/ Biochemistry/Bacteriology/Pharmacology/ Serology / Molecular Biology/Physiology from any recognized University with at least 60% marks.
Age Limit: 30 Years

How to Apply: Duly filled-in applications in prescribed application format along with copies of required documents should be reach to: Administrative Officer, National Institute of Biologicals (Ministry of Health & Family Welfare), A-32, Sector-62, Institutional Area, Noida-201309. Click here to obtain application form.

The Last Date to apply to NIB Job is 01 July 2015.

Click here to view details http://nib.gov.in/Advt%20%20%2824.04.2015%29.pdf

https://en.wikipedia.org/wiki/Sankey_diagram

Address of the bookmark: https://christophergandrud.github.io/networkD3/#sankey

Title of project- "Analysis of the structures of known antimicrobial peptides using machine learning algorithms and molecular dynamics simulations".
Name of the Post- Senior Research Fellow
No. of vacancy- One
Stipend- Rs. 14000/ +30% HRA
Essential qualification- Candidate should be having M.Sc. degree in Life Sciences / Bioinformatics / Pharmacology/ Chemistry or any other relevant area of Biology and 2 years of research experience.
Desirable- Candidate with Good knowledge of protein structures, docking, MD simulations will be preferred.
Age Limit- Not exceeding 35 Years
Duration of project- Upto April 2016
How to Apply- Interested candidates can download the application form from below mentioned link- http://www.nirrh.res.in/links/BiodataForm.pdf
Candidate must bring the filled up application form along with all the relevant documents in original and one set of attested photocopies of the same and one passport size recent colour photograph.

Ref. - http://www.nirrh.res.in/links/job_jrf-srf.htm

Address of the bookmark: https://github.com/knausb/vcfR