Applications are invited from individuals who have high motivation to do research for the below mentioned position,

1. Research Associate - 1 No.
in the DBT sponsored project under the supervision of Dr. D. Prabaharan, Principal Investigator, National Facility for Marine Cyanobacteria, Dept. of Marine Biotechnology, Bharathidasan University, Tiruchirappalli-24.

Title of the Project: “Establishment of National Repository for Micro algae & Cyanobacteria” funded by Department of Biotechnology, Govt. of India

Qualification

1. Research Associate – 1 No. Rs. 36,000/38,000/40,000 per month for I, II and III year + 20% HRA

Essential : Doctoral degree in relevant subject from recognized University/ Institutes
Desirable: Research experience in molecular biology and bioinformatics

Interested candidates can send their complete CV in plain paper with a passport size photograph, with details of Marks secured in all subjects from plus two stage (with proof, full postal address, sex, date of birth, community etc., along with additional qualification or experiences and two address of references whom could be contacted (One of whom should be PG teacher/guide). Application should reach the Principal Investigator on or before 30.06.2015 by Email (nfmcbic@yahoo.com)/Registered post/ Speed post, with subject subscribed as “Application for Research Associate /Technical Assistant /Lab attendant”. Qualifying candidates will be short listed and communicated with date of interview. No TA and DA will be given for attending the interview. Addressfor Communication Dr. D. Prabaharan Principal Investigator National Facility for Marine Cyanobacteria Bharathidasan University Tiruchirappalli-620024, Tamil Nadu.

Advertisement: http://www.bdu.ac.in/adv/NFMC_Project_Positions.pdf

• Using state of the art tools, easily extended for other viruses

• Tool and database updates for critical components via Conda

• Built using modern design patterns with Conda and Snakemake

• Extensible and easy to customize

• Submission Ready Genomes

• Customizable reporting with comprehensive visualization

https://ikim-essen.github.io/uncovar/

Github https://github.com/IKIM-Essen/uncovar

Address of the bookmark: https://ikim-essen.github.io/uncovar/

The Power of Evo 2: AI Meets DNA

Evo 2 is the largest AI model for biology ever created, trained on an astonishing 9.3 trillion DNA "letters" (nucleotides) carefully selected from genomes spanning the entire tree of life. This massive dataset ensures that Evo 2 can recognize patterns and relationships in genetic sequences at an unparalleled scale.

For the first time, scientists can design DNA with AI, moving beyond simple sequence analysis to active DNA generation. Evo 2 enables researchers to predict, modify, and even create entire genetic sequences, opening new possibilities in medicine, agriculture, and synthetic biology.

Decoding the Dark Genome

One of the biggest challenges in genetics is understanding the non-coding regions of DNA—vast stretches of the genome that do not code for proteins but play crucial roles in regulating gene expression. These regions control when and how genes are activated, influencing everything from development to disease.

Evo 2 is designed to decode these non-coding elements, helping researchers uncover their functions and use this knowledge to develop gene-based therapies, synthetic life forms, and precision agriculture solutions.

From Reading DNA to Writing It

To put Evo 2’s impact into perspective:

• Previous AI models could "read" DNA like a book, analyzing genetic sequences and identifying patterns.
• Evo 2 can "write" entirely new DNA, designing functional genes, chromosomes, and even full genomes from scratch.

This means scientists can now engineer biological systems with AI, designing new proteins, metabolic pathways, and genetic circuits to address real-world challenges.

A Step Toward Generative Biology

The Arc Institute describes Evo 2 as a major step toward "generative biology"—a revolutionary approach where AI is used to create novel biological structures rather than just analyzing existing ones. This could lead to breakthroughs such as:

• New medicines: AI-generated enzymes and proteins tailored for targeted therapies.
• Disease-resistant crops: Genetically optimized plants for higher yield and climate resilience.
• Synthetic organisms: Custom-designed microbes for bioremediation, biofuel production, and industrial applications.

An Open-Source Revolution

Unlike many proprietary AI models, Evo 2 is open source, making its capabilities accessible to researchers worldwide. This democratization of AI-driven biology means that scientists from different disciplines can collaborate, experiment, and innovate, accelerating discoveries in genetic engineering and synthetic biology.

With Evo 2, the boundaries of what’s possible in DNA design, genetic engineering, and biological innovation are being redrawn. The future of life sciences is no longer just about understanding life’s code—it’s about writing it.

The candidate is expected to have experience in handling functional genomics tools to dissect defense responses against bacterial pathogens and drought stress tolerance. This project may involve use of bioinformatics tools, database development, large scale transcriptome profiling, virus-induced gene silencing and any other research work as assigned by the PI.

Qualification: Candidates having a Ph. D. degree in Bioinformatics/Plant Molecular Biology/Plant Physiology/Plant Pathology/Plant Breeding & Genetics and strong publication record can apply. Candidates having prior work experience in using advanced molecular biology tools in laboratory with strong bioinformatics knowledge are preferred.

The Fellowship amount for the position will be given at par with the similar fellowships by DBT/DST.

NIPGR reserves the right to select the candidate against the above post depending upon the qualifications and experience of the candidate. Reservation of post shall be as per Govt. of India norms.

Eligible candidates may apply by sending hard copy of complete application in the given format with a cover letter showing interest and specifying the position. The attested copies of the mark-sheets, certificates, proof of research experience/publications are to be attached. The application should reach at the address given below within 15 days from the date of advertisement. The envelope must be superscribed by "Application for the post of RA under NIPGR Short-term research fellowship programme". No TA/DA will be paid for attending the interview.

ONLY hard copy of the application in the given format will be accepted.
www.nipgr.res.in/files/careers/format_RA2.doc

Dr. Senthil-Kumar Muthappa
Staff Scientist - III,
National Institute of Plant Genome Research (NIPGR)
Aruna Asaf Ali Marg, P.O. Box NO. 10531,
New Delhi - 110067

You might learn a lot about that house—the rooms, the doors, the furniture—but you would miss the bigger story: the streets, the neighborhoods, and all the ways the city changes from one place to another.

Something similar happens when scientists study bacterial genomes one at a time.

Over the past decade, researchers have collected thousands of bacterial genomes. These genomes contain an enormous amount of information about how bacteria survive, adapt, and evolve. But comparing thousands of individual genomes can quickly become a computational maze.

That is where PANORAMA enters the story.

Developed by Jérôme Arnoux and colleagues, PANORAMA is a computational tool designed to explore bacterial pangenomes—the complete collection of genetic possibilities found across a species or group of related organisms. Instead of looking at every genome as an isolated object, the approach represents their shared and variable genetic features as a graph.

Think of this graph as a giant subway map.

Some stations appear on almost every route. These represent genes that are highly conserved. Other stations appear only on certain routes, representing genes that some bacteria possess while others do not. By looking at the entire network, scientists can begin to see not just *what genes exist*, but how they are organized and how biological systems are distributed across populations.

The researchers put PANORAMA to the test using 941 genomes of Pseudomonas aeruginosa, a bacterium important in human health. They used the tool to investigate biological systems, including bacterial defense mechanisms against viruses known as bacteriophages. They then expanded the analysis to more than 6,000 genomes from four Enterobacteriaceae species.

The result is more than a faster way to process data.

PANORAMA allows researchers to ask a bigger question: What can an entire microbial species do, genetically speaking?

By comparing pangenomes, the researchers could identify systems shared between species as well as distinctive features. They could also find recurring genomic locations where genetic material is inserted—clues that may reveal common evolutionary processes.

And this is perhaps the most exciting part of the story.

Every bacterial genome is like a page in a huge evolutionary book. Until recently, reading thousands of those pages together was difficult. PANORAMA provides a way to turn those pages into a map, allowing scientists to see patterns that might disappear when each genome is studied separately.

The study, published in PLOS Computational Biology in July 2026, presents PANORAMA as a foundation for large-scale comparative pangenomics. The software and accompanying analysis resources are openly available, giving other researchers the opportunity to explore microbial diversity themselves.

So the story is not really about one bacterium or one genome.

It is about changing the way we look at life.

Instead of asking, “What is inside this genome?”, scientists can increasingly ask, “What is the full genetic landscape of this species—and how did it become this way?”

And sometimes, when you stop looking at one house and finally see the whole city, the most interesting discoveries are hiding in the streets between them.

Read more at https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1013856

A recent study by Webster and Chapman introduces Buscogeny (https://github.com/Jwebster89/Buscogeny), an open-source bioinformatics pipeline designed to make this process easier. The tool uses BUSCO (Benchmarking Universal Single-Copy Orthologs), which identifies conserved genes that are expected to occur as single copies in particular groups of organisms. These genes act like evolutionary landmarks, allowing researchers to compare genomes and investigate their relationships.

Buscogeny brings several steps of phylogenomic analysis into one workflow. It identifies BUSCO genes, extracts and aligns their sequences, removes unreliable regions, combines information from multiple genes, and uses the resulting data to construct a phylogenetic tree. It also provides quality-control information, helping researchers identify genomes that may be too incomplete for reliable analysis.

The authors demonstrate the usefulness of Buscogeny with bacterial and fungal genomes, including Alternaria. This is particularly valuable because fungal genomes can vary greatly in quality and annotation. Ultimately, Buscogeny helps transform massive amounts of genomic data into an understandable evolutionary story. Each DNA sequence becomes a clue, each conserved gene becomes a landmark, and together these clues reveal a picture of how life is connected.

More at https://link.springer.com/article/10.1007/s10123-025-00752-6?

Assam Applications are invited for Walk-in-Interview for the following temporary positions in the MHRD sponsored Centre of Excellence under FAST project entitled “Machine Learning Research and Big Data Analysis” under the Principal Investigator Professor D.K. Bhattacharyya, Department of Computer Science & Engineering, Tezpur University.

Position : Senior Research Fellows (SRFs) in the field of (i) Bioinformatics (ii) Natural Language Processing / Speech Processing (iii) Cognitive Radio Networks / Optical Networks (iv) Network Security. No. of Positions : Five (05).

Qualification : First class in ME / M. Tech. in CSE / IT / ECE with research experience in relevant fields of research. Candidates having valid GATE / NET score shall be preferred.

Fellowship : Rs. 18,000/- (Rupees Eighteen Thousand) only per month.

Duration : Two (02) years and may be extended depending on status of the project.

Position : Junior Research Fellows (JRFs) in the field of Bioinformatics

No. of Positions : One (01).

Qualification : First class in B. Tech. in CSE / IT/ ECE or MCA with consistently good academic records. Candidates with M. Tech. in CSE / IT / ECE shall be preferred.

Fellowship : Rs. 12,000/- (Rupees twelve Thousand) only per month.

Duration : Two (02) years and may be extended depending on status of the project.

Interested candidates may send their application on plain paper by post along with his/her educational qualifications, research experience certificates (for Senior Research Fellow), 02 copies of recent passport/stamp size photograph and contact phone number to Prof. D.K. Bhattacharyya, Principal Investigator, Department of Computer Science & Engineering, Tezpur University, Napaam- 784028 or mail it to dkb@tezu.ernet.in (or to smh@tezu.ernet.in) within 15 days of publication of this advertisement.

Advertisement: www.tezu.ernet.in/ProjectWalkin/Advt_CoE_5816-A.pdf

More at https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2745767/

Address of the bookmark: http://synorth.genereg.net/

Applications are invited for the post of Senior Research Fellow- SRF (one) and Junior Research Fellow- JRF (one) to be appointed in a SERB-funded major research project entitled “Biochemical and functional properties of Synechocystis Glutathione S-transferase(s)” sanctioned to Dr. Timir Tripathi, Molecular and Structural Biophysics Laboratory, Department of Biochemistry, NEHU, Shillong.

Essential Qualifications: For both positions M.Sc. or equivalent with a good academic record is a prerequisite.

For Project-SRF, experience in bioinformatics/computational biology is required, which should be evident by publications.

Students waiting for their last semester result can apply for JRF position.

Stipend: As per SERB norms.

Interested students can email their detailed bio-data including mobile number and recent photograph to msb.biochem@gmail.com, latest by 01.08.15. The hard copy is not required at this stage.

The date of interview will be informed after primary scrutiny of the applications. No TA/DA will be paid if called for interview. P.S: Students applied for the same post as per date 01.06.15, need not to apply again as their application will be considered in this advertisement also.

For details of the research work of the PI’s group kindly visit www.ttripathi.webs.com

Dr. Timir Tripathi Principal Investigator DST-SERB Project Department of Biochemistry NEHU, Shillong

Advertisement: www.nehu.ac.in/Advertisements/BiochemPVAdvtTT_200715.pdf

This bookmark is created to provide NGS online books links.

Address of the bookmark: http://en.wikibooks.org/wiki/Next_Generation_Sequencing_%28NGS%29/Print_version