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. Work to establish improved quantitative experimental assays (such as microarrays or differential in-gel electrophoresis) and
2. Development of modern computational methods (such as hierarchical probabilistic models or integration of heterogeneous data sources)

Lab page @ http://bioinf.boku.ac.at/

Address of the bookmark: http://www.genengnews.com/keywordsandtools/print/3/32115/

Please add ur links/bookmarks in comment section.

Address of the bookmark: http://physicsdatabase.com/free-math-books/

• 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

Address of the bookmark: http://bioinformatics.oxfordjournals.org/content/23/14/1713.full

genomic scale studies
endogenous mechanisms of mutations, germ line and somatic
computational aspects of immunology in cancer
signalling networks
three-dimensional organization of information in the nucleus
gene silencing
metastatic cross-talk
kinase signaling
personalized medicine
detection of biomarkers in cancer
historical DNA variation

From : http://www.ous-research.no/hovig/

Group address:
Eivind Hovig, The Norwegian Radium Hospital, Montebello, 0310 Oslo,Norway
Email: ehovig@radium.uio.no

CENTRE FOR BIOINFORMATICS

PUDUCHERRY

Applications are invited for one Project Assistant to work in the UGC sponsored Research Award "Molecular Docking and Dynamics studies to understand the interacting mechanism of oncogenic 101 protein with its cellular proteins".

The duration for the fellowship is 12months only with consolidated pay ofRs. 5,000 per month.

Application on plain paper with following details: Name, Address, Data of Birth, Father's Name, Nationality, Educational Qualification (SSLC onwards-enclose attested copies of certificate) and Researcb Experience may be addressed to Dr. R. Krishna, Principle Investigator (PI), UGC Research Award, Centre for Bioinformatics, Pondicherry University, Pondicherry - 605 014.

Application should reach in January 261h , 2013.

Essential Qualification: M.Sc. in Bioinformatics/Biophysics with good academic record.

Qualification for Project Fellow:

M.Sc in Bioinformatics/Biophysics.

The person to be considered for appointment as Project Fellow must have second class master degree with a minimum of 55% marks in the subject concerned or a related subject.

The candidate to be appointed as Project Fellows should be below thc age of40 years at the time of appointment.

Desirable Qualification for this Project: Research Experience in Small/Macromolecule Crystallography and Structural Bioinformatics.

For more details, refer the web site: www.pondiuni.edu.in/sites/default/files/BIC-311213.pdf

High Throughput Sequencing Analysis
Comparative Genomics
Identification and Annotation of Non-coding RNAs
Bioinformatic Analysis and System Biology of Viruses
Coevolution of Proteins and RNAs
Algorithmic Bioinformatics
Phylogenetic Analysis

http://www.rna.uni-jena.de/index.php

(Under Tenure-Track Model)

Open Advt. No IIITA/DIC/16012014

IIIT-Allahabad has several Openings for the Faculty positions at the Assistant Professor level.

It is a regular tenure-track faculty positions for 3-5 years in teaching and research. A regular faculty is expected to engage heavily in research and teaching. The eligibility criteria for regular faculty positions are similar as in IITs. For an Assistant Professor position, a candidate must have a PhD (in IT/Computer Science &/or Engineering/Electrical, Electronics &/or Communication Engineering/etc; for interdisciplinary areas the PhD may be in an appropriate field), plus three years experience. However, for PhDs from a well known University/Institute (e.g. IITs/IISc/TIFR/ISI in India or well known research universities across the world), and a good research/academic record, the 3 years experience requirement may be waived.

The pay scale for faculty is same as in IITs. Other benefits include initiation research grant, travel support, book grant, professional society membership, etc., and personal benefits such as medical/LTC, on campus subsidized family housing with excellent modern infrastructural facilities.

Areas of Interest

IIIT-Allahabad aims to build strong research groups in important and emerging areas in CS/IT/ECE as well as in emerging interdisciplinary areas, and applications are invited in all these areas. Some of the areas of special interest, besides strengthening the existing research areas, are : Software Engineering, Theoretical Computer Science, Cyber Physical Systems, Robotics, Network science, Digital Media, Computational neuroscience, Machine learning, Healthcare informatics, Computational Biology, Communications networks (both at hardware and protocol levels), Circuits (including VLSI, analog, low power, etc), Energy systems and technologies, Biomedical electronics and systems, Computer Architecture, signal/image processing, Embedded and control systems.

Application Process

Interested candidates can apply by sending their detailed CV with list of publications clearly mentioning Journal names and citation index with three references through email entitled “Faculty positions at IIIT Allahabad” to faculty.applications@iiita.ac.in. Do not send your applications in any other email addresses. Applications will be considered regularly, hence there is no deadline for applying.

Important Clarifications on Eligibility

A PhD in CS/IT (or other disciplines, as announced) is the minimum expected requirement for an Assistant Professor.

Advertisement: http://iiita.ac.in/pub/Faculty-Position-IIITA1.pdf