BOL: Related items

Finding the Hidden Switches: The Story of KiNext and Protein Kinases

LEGE — Thu, 24 Sep 2026 02:51:28 -0500

Every newly sequenced genome contains thousands of proteins, but identifying what each protein does is a much harder task. Among these proteins are protein kinases, important molecular regulators that control processes such as cell growth, development, metabolism, stress responses, and signaling. Finding these kinases and determining which families they belong to can reveal important clues about how an organism functions and has evolved.

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.

Bioinformatics market in India

Rahul Agarwal — Fri, 23 Aug 2013 07:08:49 -0500

Key Topics Covered in the Report:

The market size of the Indian Bioinformatics Industry , FY’2007-FY’2013
Market segmentation of India bioinformatics industry by application by sectors, FY’2007-FY’2013
Market Segmentation of India bioinformatics industry by products and services,FY’2007-FY’2013
Market Segmentation of India bioinformatics industry by applications of bioinformatics ,FY’2007-FY’2013
India bioinformatics industry trends and developments
Government regulations and initiatives of India bioinformatics industry
Major bioinformatics research institutes in India
Market Share of leading players in bioinformatics industry in India,FY’2013
Company profiles of major players in India bioinformatics industry
Future outlook and projections on the basis of revenue in India bioinformatics market, FY’2014-FY’2018

(Source: Ken Research)

Address of the bookmark: http://www.kenresearch.com/healthcare/biotechnology/india-bioinformatics-industry-research-report/392-91.html

Asst. PROF IN BIOINFORMATICS at JAIPUR NATIONAL UNIVERSITY

Thu, 12 Sep 2013 07:18:02 -0500

JAIPUR NATIONAL UNIVERSITY, SCHOOL OF LIFE SCIENCES (SIILAS CAMPUS) URGENTLY REQUIRES

Asst. PROF IN BIOINFORMATICS.

QUALIFICATION: AS PER UGC

DESIRABLE: 1 YEAR EXPERIENCE IN ACADEMICS

CONTACT immediately

Prof D.S.Bhatia
Director
9351288070

Last date within 7 days of the publication.

Find more @ http://jnujaipur.ac.in/downloads/AdvtDec2012.jpg

Research Associate@ School of Computational and Integrative Sciences under Jawaharlal Nehru University

Fri, 22 Nov 2013 19:06:44 -0600

School of Computational and Integrative Sciences under Jawaharlal Nehru University, New Delhi invited applications for filling up 4 posts of Research Associates (RA) and Junior Research Fellow (JRF) (2 posts each) purely on temporary basis, liable to be terminated at any time without prior notice or ceased/withdrawn by the funding agency. The vacancies are for a Department of Biotechnology, Government of India funded project entitled "Computational Core for Plant Metabolomics" (Project ID: 632) being administered by Prof Indira Ghosh. Interested candidates should send their applications till 13 December 2013.
Important Dates
Last Date for receipt of applications: 13 December 2013
Vacancy Details
Total Vacancies: 4 posts
Type of recruitment: Temporary
Sl. No.: 01
Name of the Post: Research Associate
No of Posts: 1 post
Remuneration: Rs. 23000 + 30%
Qualifications: PhD in Bioinformatics / computational biology / Biophysics / Physical Chemistry / Computer Science. Computational experience, proven by paper published, is a necessary qualification.
Sl. No.: 02
Name of the Post: Research Associate
No of Posts: 1 post
Remuneration: Rs. 23000 + 30%
Qualifications: PhD in Computational Biology / Bioinformatics & related subjects. Computational experience, proven by paper published, is a necessary qualification.
Sl. No.: 03
Name of the Post: Junior Research Fellow
No of Posts: 1 post
Remuneration: Rs. 12000 + 30%
Qualifications: M. Sc. / B. Tech. preferably in Computational Biology /Bioinformatics and related fields with experience in Website designing & maintenance of Database.
Sl. No.: 04
Name of the Post: Junior Research Fellow
No of Posts: 1 post
Remuneration: Rs. 12000 + 30%
Qualifications: M. Sc. / MCA / B. Tech. preferably in Computational Biology / Computer science with experience in Programming in Java / Python, C++ etc & designing of Database.
Selection Procedure: Selection will be done on the basis of candidates’ performance in the Interview.
Candidates short-listed / selected for Interview will be informed through email only.
How to Apply: Interested eligible candidates should send their applications, in the prescribed format, along with their current CV by post to “Prof Indira Ghosh, Project Investigator, Hall#6, School of Computational and Integrative Sciences, Jawaharlal Nehru University, New Delhi-110 067” so as to reach the concerned authority by 13 December 2013.
Name of the post applied for’ must be superscripted on the envelope containing the application.
NOTE: For the post of Research Associates, only those candidates who have submitted thesis are eligible to apply. However, salary will be provided as per DBT / DST guidelines (i.e. candidates who have qualified NET /BET / BINC will have higher pay scale).
Candidates interested to register for PhD may not apply for JRF.
More @ http://www.jnu.ac.in/Career/currentjobs.htm

Candidates required in Bioinformatics and Genomics UK ONLY

Fri, 03 Jul 2015 08:22:41 -0500

I have various permanent positions available based in London, Manchester, Herftfordshire, Oxford and Belfast, as well as other areas throughout the UK.

If you are looking for a new opportunity and have skills within any sector of Bioinformatics with an IT skill then I would love to hear from you. I have various exciting opportunities from programmers to researchers to scientists.

Call me now on 01772 278050 or email me your cv and requirements and I will call you back dareen.evans@itworkshealth.co.uk

Murray Cox's Genomicus Lab

Thu, 26 Sep 2013 16:42:42 -0500

This group interested in modeling genome dynamics in following topics:

---how genetic variation is distributed within and between individuals,
---determining how this diversity changes over evolutionary time.

Hence, Cox group work at the interface between biology, statistics and computer science to address questions of outstanding biological importance through intrepretation of large genetic datasets.

Profile:
Associate Professor Murray Cox,
Inaugural Rutherford Fellow of the Royal Society of New Zealand, Principal Investigator in the BioProtection Research Center and Associate Investigator in the Allan Wilson Center for Molecular Ecology and Evolution
Email : m.p.cox@massey.ac.nz
Webpage: http://massey.genomicus.com/index.html

04- Informatics Approach to Cancer - Interview with Dr. Joel Saltz

Mon, 07 Oct 2013 14:35:43 -0500

For additional information visit http://www.cancerquest.org/joel-saltz-interview. Dr. Joel Saltz is a Professor in the Departments of Pathology, Biostatistics and Bioinformatics, and Mathematics and Computer Science at Emory University. Dr. Saltz's research on bioinformatics spans several disciplines. One project involves applying computer analysis to medical imaging to yield better results for patients. As an example, a computer program may able to help doctors detect small cancers in a CT scan or mammogram. In this interview segment, Dr. Saltz discusses the informatics approach to cancer. To learn more about cancer and watch additional interviews, please visit the CancerQuest website at http://www.cancerquest.org.

Evolution and Cancer

Fri, 27 Sep 2013 11:28:49 -0500

Air date: Wednesday, January 04, 2012, 3:00:00 PM Time displayed is Eastern Time, Washington DC Local Category: Wednesday Afternoon Lectures Description: There is a broad consensus that cancer is the result of somatic cells having serially gained, by a series of mutations, the ability to grow independently, to recruit resources from the circulation and the stroma, to invade local tissues, and to found anatomically distant metastases, ultimately killing the host. From the point of view of the cancer-causing somatic cell population, this is evolution driven by mutation and selection. Genomics has resulted in a parallel consensus that the central functions of all eukaryotes are highly conserved, not only at the level of individual protein functions, but also complex biological pathways and systems. These ideas motivated a comparison between results of molecular genetic studies of experimental evolution in yeast and the molecular genetic phenomena associated with tumorigenesis and tumor progression. We find some very striking similarities, including recurring genomic rearrangements, alterations of the regulation of specific growth-promoting genes, population-genetic features that affect the fitness trajectories of growth rate variants in evolving populations, and physiological and metabolic similarities derived from the conservation of the basic plan of growth and cell multiplication among all eukaryotes. It is hoped that some of the insights from yeast will aid the interpretation of sequence changes found in tumors, especially in the urgent necessity to distinguish 'driver' from 'passenger' mutations." David Botstein's fundamental contributions to modern genetics include the development of genetic methods for understanding biological functions and the discovery of the functions of many yeast and bacterial genes. In 1980, Botstein and three colleagues proposed a method for mapping human genes that laid the groundwork for the Human Genome Project. The basic principle of the mapping scheme was to develop, by recombinant DNA techniques, random single-copy DNA probes capable of detecting DNA sequence polymorphisms when hybridized to restriction digests, or specific fragments, of an individual's DNA. The method was used in subsequent years to identify several human disease genes, such as Huntington's and BRCA1. Variations of this method enabled the sequencing phase of the Human Genome Project. In the 1990s Botstein, having moved to Stanford University School of Medicine, collaborated with Patrick O. Brown of Stanford in exploiting DNA microarrays to study genome-wide gene expression patterns in yeast and in human cancers. This required developing a new statistical method and graphical interface, widely used today to interpret genomic data. Botstein also has helped to create, with Michael Ashburner and Gerald Rubin, a bioinformatics initiative to unify the representation of gene and gene product attributes across all species, called Gene Ontology. He graduated from Harvard College and earned his doctorate from the University of Michigan. He worked at Massachusetts Institute of Technology from 1967 to 1988; served as vice president for science at Genentech from 1988 to 1990; chaired the Department of Genetics at the Stanford University School of Medicine from 1990 to 2003; and joined the Princeton University faculty in 2003. He has sat on numerous editorial boards and was the founding editor of Molecular Biology of the Cell. Among recent major awards, Bostein won the Peter Gruber Foundation Prize in Genetics in 2003, the Apple Science Innovator Award in 2008, and the Albany Medical Center Prize in 2010. The NIH Wednesday Afternoon Lecture Series includes weekly scientific talks by some of the top researchers in the biomedical sciences worldwide. For more information, visit: The NIH Director's Wednesday Afternoon Lecture Series Author: Dr. David Botstein, Princeton University Runtime: 00:59:58 Permanent link: http://videocast.nih.gov/launch.asp?17046

Pre- or postdoctoral research fellowship in Structural Bioinformatics in Padova

Wed, 02 Oct 2013 15:12:22 -0500

University of Padova (URL: http://protein.bio.unipd.it/)

A research fellowship is available at the BioComputing Laboratory, University of Padova (URL: http://protein.bio.unipd.it/). A highly motivated and creative candidate is sought to work on structural bioinformatics. Specifically, the project entails the development of novel methods, tools and databases for the analysis of protein structures. The BioComputing Laboratory is a group of a dozen people working on several aspects of prediction of protein structure & function employing techniques at the intersection between biology, medicine, chemistry, physics & computer science. Our aim is to integrate the development of novel methods and their application to biologically relevant problems. We are looking for candidates with a solid Bioinformatics background, programming experience (Python, Perl, C++ and/or Java) and good knowledge of molecular biology (protein structure/function, signalling pathways). Candidates should have a degree with top marks, optionally hold a PhD, and be highly motivated to work on interdisciplinary research. Good knowledge of English, an open-minded spirit, being collaborative and creative are crucial. The fellowship, which should start in late 2013, is initially for one year. It will be commensurate to experience, can be extended depending on performance and may lead to a PhD degree. The successful candidate will be located at the BioComputing Laboratory, University of Padova. Travel support for conferences and/or research visits abroad may be provided. To apply, please send your CV, a brief description of your research background and the names of two (or more) references to Prof. Silvio Tosatto (Email: silvio.tosatto@unipd.it).

Contact Person (Referent): Silvio Tosatto
Ref. E-Mail: silvio.tosatto@unipd.it
Tel: +39 049 827 6269
Fax: +39 049 827 6260
Group Web Page: http://protein.bio.unipd.it/

Amity University Bioinformatics Summer Program - Kolkata

eliabrodsky — Tue, 11 Jun 2019 21:27:10 -0500

Registrations are now open for the 2019 Summer Bioinformatics Training program at Amity University, Kolkata. The program will focus on introductory topics for life science students. We will review important history, topics and challenges bioinformatics can help address in the context of basic research, discovery and industry.

Read more: https://edu.t-bio.info/amity-university-summer-bioinformatics-program-registrations-are-open/