the study of the sequence-structure relationship
(application -> structure prediction)
the study of the structure-function relationship
(application -> function prediction)

Therefore, anything related to the configuration (sequence) and conformation (structure) in atomic systems of proteins and nucleic acids, and the interaction of these with other elements (function) is of our major interest.

Lab page @ http://melolab.org/mbl/

This is where KiNext comes into the picture. Introduced in a 2024 study published in BMC Bioinformatics, KiNext is a computational workflow designed to identify and classify protein kinases from predicted protein sequences. Instead of relying on a single search method, it brings together several approaches, including Hidden Markov Models, sequence alignment, phylogenetic analysis, and structural comparison.

The search begins with a simple question: does a protein contain the characteristics of a kinase? Protein kinases can change considerably during evolution, but important regions of their sequences often retain recognizable patterns. KiNext uses Hidden Markov Models, or HMMs, to detect these patterns. An HMM does not require a protein to be an exact match to a known kinase. Instead, it looks for a statistical sequence signature associated with kinase proteins, making it possible to detect more distant candidates.

Once potential kinases are identified, KiNext takes the analysis further. It distinguishes conventional eukaryotic protein kinases from atypical protein kinases and then attempts to classify them into different kinase groups and families. This distinction is important because simply identifying a protein as a kinase does not tell the complete story. Different kinase families can have very different evolutionary histories and biological functions.

The next stage brings evolution into the picture. KiNext can align kinase sequences and construct phylogenetic trees, allowing researchers to examine how newly identified proteins are related to previously characterized kinases. When sequence evidence alone is difficult to interpret, structural information can provide another clue. The workflow can incorporate AlphaFold-predicted structures and Foldseek-based structural comparisons to investigate whether an unusual protein resembles known kinase structures.

The researchers tested KiNext using two very different organisms: the Pacific oyster, Crassostrea gigas, and the green alga Ostreococcus tauri. In C. gigas, KiNext recovered previously reported kinases while identifying additional candidates. Structural analysis provided further evidence for many of the newly detected proteins. In O. tauri, the workflow similarly recovered most previously reported kinases and identified additional candidates while refining some of their classifications.

What makes KiNext particularly interesting is not just its ability to find kinases, but how the entire analysis is organized. The workflow uses Nextflow, allowing the different computational steps to be connected into a reproducible pipeline. Containers can also help manage software dependencies, making it easier to run the workflow across different computing environments.

This reproducibility becomes increasingly important as the number of available genomes continues to grow. A researcher studying one organism may be able to perform an analysis manually, but repeating the same process across hundreds or thousands of genomes quickly becomes impractical. A standardized workflow provides a way to perform the analysis consistently while keeping track of how the results were generated.

At its core, KiNext demonstrates a broader change taking place in modern genomics. Sequencing a genome provides an enormous amount of information, but the real scientific challenge begins afterward: understanding what all those sequences mean. Protein kinases are only one part of this larger puzzle, yet they are particularly important because they act as molecular switches throughout the cell.

By combining sequence profiles, evolutionary analysis, and structural evidence within a reproducible computational framework, KiNext provides researchers with a systematic way to uncover these molecular switches. Its real value lies not only in finding more kinases, but in making the process scalable, repeatable, and easier to apply to new genomes.

As genome sequencing continues to expand across the tree of life, tools such as KiNext can help turn enormous collections of protein sequences into meaningful biological stories—one kinase at a time.

Read more about it @

https://link.springer.com/article/10.1186/s12859-024-05953-w

1 Scientist E 3

50,000/-

M.Sc. in Life sciences or Plant Sciences or Biotechnology or Microbiology or Bioinformatics or Ph.D. from a recognized university in any of above subject.

Minimum 8 Yrs. of experience after M.Sc. or 5 Yrs. of experience after Ph.D. in responsible position of work in R & D in the area of genomics/ conservation biotechnology/bioinformatics/Planning/Scientific Administration in Science and technology organization. Highly qualified in the area of modern biology, as evidenced through research experience and proven ability to carry out work in the area of conservation biotechnology. Age limit not exceeding 40yrs.

2 Scientist B 6

30,000/-

M.Sc. in Life sciences or Plant Sciences or Biotechnology or Microbiology or Bioinformatics or Ph.D. from a recognized university in any of above subject shall be preferred.

Minimum 3 Yrs. of experience after M.Sc. in responsible position of work in R & D in the area of genomics/ conservation biotechnology/ bioinformatics /Planning/Scientific Administration in Science and technology organization. Highly qualified in the area of modern biology, as evidenced through research experience and proven ability to carry out work in the area of conservation biotechnology. Age limit not exceeding 35yrs.

The positions are purely on contractual basis for 11 months. Interested candidates can apply online in specified format available at "http://leogen.in/recruit/" The last date of applying is 24th December, 2013. Applications must be submitted online only. Applications submitted in any other format except online prescribed performa will be rejected. Candidates in service must apply through proper channel. Candidates will be required to provide original documents along with duly filled and signed application Performa, as and when called for interview.

For more details please visit the website URL : http://leogen.in/recruit

Address of the bookmark: http://www.ogt.com/assets/0000/3190/NGS_Survey_2013_Infographic_Web.pdf

Lab Page http://gabi.cidbio.org/index/

Source:  Igor Ulitsky & Ron Shamir

Address of the bookmark: http://acgt.cs.tau.ac.il/guides/LiteratureGuide.htm

Translational recoding.

RNA editing.

Evolution of the genetic code and translation.

More at http://lapti.ucc.ie/research.html

Lab page http://lapti.ucc.ie/index.html

PNAS papers:
http://www.pnas.org/search?author1=Janet+Kelso&sortspec=date&submit=Submit

Jobs:
http://www.eva.mpg.de/genetics/bioinformatics/jobs.html

Contact:
Kelso Group
Department of Evolutionary Genetics
Max Planck Institute for Evolutionary Anthropology
Deutscher Platz 6
04103 Leipzig
Germany
Email: kelso@eva.mpg.de

Name of the fellowship: Junior Research Fellow (JRF) / Project Fellow

Title of the project: Genome-wide Mapping of Murine Specific Dengue T-cell Epitopes: Computational Prediction, Identification and use as Candidate Vaccines

Duration: 3 years

Fellowship: Rs. 18,000 for first 2 years and Rs. 20,000 for 3rdyear (for M.Tech. candidates)

Rs. 16,000 for first 2 years and Rs. 18,000 for 3rdyear (for M.Sc. candidates with NET qualification)

Rs. 8,000 for first 2 years and Rs. 10,000 for 3rdyear (for M.Sc. candidates without NET qualification)

Qualifications: M.Tech. in Biotechnology / M.Sc. in any branch of Life Sciences

Desirable Experience: Minimum of two years research experience in any of the following areas: Immunology / Microbiology / Gene Manipulation / Bioinformatics

Interested and eligible candidates may apply with their resume along with relevant documents and a passport size photograph to the Principal Investigator by post (or e-mail) on or before December 31, 2013. Only short listed candidates will be called for written test and/or interview. Selected candidate may register for PhD in Kalasalingam University. No TA/DA will be paid for attending interview.

Dr. K. Sundar
Principal Investigator (SERB Project)
Department of Biotechnology
Kalasalingam University
Krishnankoil – 626126, Tamil Nadu
sundarkr@klu.ac.in

"Computational Methods for the Analysis of the Diversity and Dynamics of Genomes"

has currently open positions for graduate students, to study at Simon Fraser University (Vancouver, Canada) and
Bielefeld University (Germany), starting in the fall 2014.

This international graduate program is a close cooperation of:

Bielefeld University, Germany: Graduate progam "DiDy"
Simon Fraser University (SFU), Vancouver, Canada: Graduate program "MADD-Gen"

The available positions include six PhD positions at Bielefeld University, as well as PhD and MSc positions at SFU.

Application deadline: December 31st, 2013
Webpage: http://wiki.techfak.uni-bielefeld.de/didy/Announcement