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:

DEPARTMENT OF BIOTECHNOLOGY

No. NITW/Bio/ Date: 30th March 2015

ADVERTISEMENT FOR PROJECT FELLOW (Research Staff)

Applications are invited for the post of Project Fellow (Research Staff) for the project entitled ‘Metagenome derived nitroreductases for degradation of nitro compounds’ sponsored by the Department of Science and Technology (DST-INSPIRE), Govt. of India.

Position: Project Fellow (1 No.)

Project Duration: 5 years

Note: The post is purely on temporary basis for a period one year and may be extendable till the end of the project based on the progress of the candidate.

Emoluments: Rs. 14,000/- per month (Consolidated) for first two years and Rs. 16,000/- per month (Consolidated) for next three years.

Essential Qualifications:

i) First class in M.Tech/M.S (Biotechnology/Industrial Biotechnology/Bioinformatics) or equivalent. Or

ii) First class in M.Sc. (Biotechnology/Bioinformatics/Biochemistry/ Microbiology/Molecular biology).

Desirable Qualification: Preference will be given to candidates who have cleared NET/GATE or having prior work experience in Molecular biology/Bioinformatics sequence analysis.

Interested candidates may submit their application in plain paper along with Curriculum Vitae and photocopies of certificates in support of educational/professional qualifications. Application should be sent in a closed cover with a superscription on the cover “Application for the post of project fellow (DST-INSPIRE)” on or before 20.04.2015 (Monday) via Post to the Principal Investigator. Eligible candidates will be intimated through e-mail and called for interview at the Department of Biotechnology, NIT, Warangal. No TA/DA will be paid for attending the interview. Dr. K. Divakar (Principal Investigator) DST-INSPIRE Faculty Department of Biotechnology National Institute of Technology Warangal – 506 004. Telangana, India. E-mail: divakar@nitw.ac.in; kdivak@gmail.com

Advertisement: http://www.nitw.ac.in/nitw/announcements/2015/Notification_Project_Fellow_DST_INSPIRE_Biotechnology_NITW.pdf

The engagement is purely temporary on contractual basis and co-terminus with the project. There will be no provision of absorption of absorption/reemployment in IVRI/DBT on termination of the project.

No TA/DA will be provided for appearing in the interview and no separate letter will be issued.

A. Name tile of the project: “Centre for Agricultural bioinformatics (CABin)”.

B. Position/post to be filled: Research Associate (one)

C. Essential/Desirable qualifications:

•Essential: M.V.Sc./M.Tech./MSc Degree in Biotechnology/ Biochemistry/ Microbiology/Immunology/Bioinformatics/Genetics/Life Sciences or

Masters in Computer Application/ Masters in Computer science with first division.

• Desirable: Experience in cell culture, next generation sequencing, C++ and perl programming. NET/GATE qualified will be preferred.

• Experience : At least 2 years

D. Emoluments: Rs. 23000/- per month + 20% HRA

E. Age Limit: Maximum 40 years for men and 45 years for women

F. Duration of the project: Up to March 2017

G. Name of PI/Contact person: Dr. G.V.P.P.S. Ravi Kumar, Sr. Scientist, Division of Veterinary Biotechnology.

H. Address for correspondence: Dr. G.V.P.P.S. Ravi Kumar, Sr. Scientist, Computational Biology and Genomics facility,Division of Veterinary Biotechnology, I.V.R.I., Izatnagar – 243122

Advertisement: www.ivri.nic.in/jobs/WalkIn_interview_01042015.pdf

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

1. “Development of bioinformatics methods for identifying novel secondary metabolites by genome mining” funded by DBT

JRF (P)/SRF (P) (One Position only)

Dr. Debasisa Mohanty Staff Scientist-VI deb@nii.res.in

Educational Qualifications: JRF (Project): M.Sc (Bioinformatics/ Biophysics/Biotechnology or any other stream of biological/physical sciences) or M.Tech. (Bioinformatics/Biotechnology/Computational Sciences) of M. Pharm.

SRF (Project): M.Sc (Bioinformatics/Biophysics/Biotechnology or any other stream of biological/physical sciences) or M.Tech. (Bioinformatics/Biotechnology/Computational Sciences) of M. Pharm with atleast 03 years of research experience.

Desirable Qualifications: Strong computer programming skills (in PERL/CGI/PHP or C++ or object oriented database management systems like MySQL etc or scripting languages under LINUX/UNIX environment) and sufficient experience in computational analysis of biological/biochemical data.

The candidates must highlight their experience in programming and database development in their CV. Job description: Computational analysis of genomes and development of bioinformatics tools and software’s for sequence and structure based analysis of biosynthetic pathways.

Emoluments: The selected candidates will draw consolidated emoluments as per Institute Rules, depending upon qualifications & experience JRF (Project): Rs. 12,000/- per month plus 30% HRA SRF (Project): Rs. 14,000/- per month plus 30% HRA (*Candidates possessing qualifications as per latest DST OM, will be given revised scales).

More at http://www1.nii.res.in/sites/default/files/projectappointments-Dr.DebasisaMohanty-30April2015.pdf

However, pangenome graphs can be highly complex, making them difficult to visualize and interpret. A recent study published in BMC Bioinformatics introduces PG2 (PanGenoGrapher), an open-source, web-based tool designed to address this challenge. The source code and user guide are openly available on GitHub at https://github.com/iVis-at-Bilkent/pangenographer. A publicly accessible sample deployment is hosted at http://pg2.cs.bilkent.edu.tr. In addition, a demonstration video illustrating the primary use cases of PG2 is available at https://www.youtube.com/watch?v=yCd7-aGY6CQ.

PG2 combines advanced graph-layout algorithms with an interactive visualization platform. It allows researchers to explore genomic paths, identify variations, and examine relationships between different parts of a pangenome graph more easily.

This is important because visualization can play a major role in bioinformatics. When complex genomic information is presented clearly, researchers can more easily identify patterns, understand genetic variation, and generate new biological insights.

The development of PG2 represents a step toward making pangenome analysis more accessible and intuitive. As genomic datasets continue to grow and graph-based representations become more common, tools like PG2 can help researchers navigate this increasing complexity.

Ultimately, PG2 demonstrates how combining genomics, graph algorithms, and interactive visualization can make sophisticated biological data easier to understand and analyze.

Reference: Solun, G. K., Dogrusoz, U., Bingöl, Z., & Alkan, C. (2026). PG2: algorithms and a web-based tool for effective layout and visual analysis of pangenome graphs. BMC Bioinformatics. DOI: 10.1186/s12859-026-06555-4.

IGIB Vacancy Details:
Total No. of Posts: 04
Name of the Posts:
1. Project Scientist (Biology): 02 Posts
2. Project Scientist (Bioinformatics): 01 Post
3. Sr Project Fellow (Ayurveda): 01 Post

Age Limit: Candidates age should be 35 years for post 1, 32 years for post 2

Educational Qualification: Candidates should have Ph.D/ Ph.D submitted in any branch of Biological Science/ Life Science for post 1, Ph.D/ Ph.D submitted in Bioinformatics for post 2, BAMS degree with one year internship for post 3.

Selection Process: Candidates will be selected based on their performance in interview.

How to Apply: Eligible candidates may send their application along with all relevant documents on or before 23-04-2015.

Important Dates:
Last Date for Receipt of Application for Post 1 & 2: 23-04-2015.
Date of Interview for Post 3: 27-04-2015.

For other details like pay scale, age relaxation, educational qualification, selection process, how to apply, etc., click on the link given below…

http://www.freejobalert.com/wp-content/uploads/2015/03/Notification-IGIB-Project-Scientist-SPF-Posts.pdf

http://www.igib.res.in/sites/default/files/27042015.pdf

Scientists face a big challenge with the human genome. They can read its letters, but understanding their roles is much harder. Only about 2 percent of the genome codes for proteins. The rest acts like a huge control panel, deciding when and where genes turn on. With about 9 billion possible single-letter changes, testing them all in a lab just isn’t possible.

So, Google DeepMind asked a new question: what if we could predict what those changes might do?

This question led to the AlphaGenome Atlas (https://deepmind.google.com/science/alphagenome/atlas?), a detailed map of nearly every possible single-letter change in the human genome. Instead of checking each change one by one, researchers can use the Atlas to spot the ones most likely to matter. The AlphaGenome Variant Impact (AVI) score works like a trail marker, pointing scientists toward the changes worth a closer look.

This is where the Atlas gets especially useful. Much of the genome lies outside the protein-coding regions, where DNA acts as a switch or controller for genes. AlphaGenome lets researchers explore these areas and see how small changes could affect gene activity.

An atlas isn't the destination; it's a guide.

The AlphaGenome Atlas doesn’t replace experiments or solve every mystery. Instead, it helps scientists decide where to begin. From billions of possibilities, it turns the vast genetic landscape into something researchers can start to explore.

There are nine billion possibilities, a vast map, and maybe among them therWith nine billion possibilities and a huge map to explore, there may be clues hidden here to some of medicine’s toughest mysteries.

More at https://storage.googleapis.com/deepmind-media/DeepMind.com/Blog/alphagenome-atlas-a-predictive-map-of-every-possible-dna-letter-change-in-the-human-genome/alphagenome-atlas.pdf