All genomes in the dataset were sequenced to at least 30x coverage using Illumina technology. The sequencing reads were mapped and genotyped using a customized procedure that was optimized for population genetic analysis. The researchers eliminated bias of alleles toward matching the human genome reference sequence, and determined genotypes on a single-sample basis to avoid preferential calling of genotypes from populations that had more individuals represented.

Address of the bookmark: https://www.simonsfoundation.org/simons-genome-diversity-project/

Address of the bookmark: https://brapi.org/

Address of the bookmark: https://phytozome.jgi.doe.gov/pz/portal.html

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.

Campaign calendar:

- Opening date for applications: January 30, 2020
- Deadline for applications: March 5, 2020
- Pre-selections: April-May 2020
- Final selections: May-June 2020
- Starting date for appointments: from September 2020

More at https://jobs.inrae.fr/en/open-competitions/open-competions-research-scientists-crcn

Address of the bookmark: https://rna.sysu.edu.cn/chipbase/

https://www.nasa.gov/reference/osdr-data-processing/

Address of the bookmark: https://www.nasa.gov/osdr/

The position is open for immediate appointment and available for two years and then extendable for additional one year. The applicant will be appointed as Research Associate based on qualifications as detailed below:

Research Associate:

-Master’s degree with bioinformatics with at least 2 years of research experience in Next Generation sequencing data analysis as evidence from Fellowship/ Associateship / Training / other engagements.

-Familiarity with bioinformatics tools, database development, programming skills

-Minimum 1 publication in any peer reviewed journal

Salary will be as per ICAR rules and guidelines. Application will be shortlisted based on CV, reference letters from mentors and telephonic interview. Candidates will be called for a personal interview at Bangalore before appointment. No travel expense will be provided for attending interview at Bangalore.

Interested candidates may send a Letter of Interest and CV by email to: keshav@ibioinformatics.org before September 29, 2015.

http://sfg.stanford.edu/denovo.html

http://sfg.stanford.edu/sequencing.html

http://sfg.stanford.edu/BLAST.html

http://sfg.stanford.edu/denovo.html 

Address of the bookmark: http://sfg.stanford.edu/guide.html

Address of the bookmark: https://www.encodeproject.org/data-standards/reference-sequences/