Evidence map›Paper›PMID 38445556›Full record

ArticleJournal of biosciences2024

Finding identical sequence repeats in multiple protein sequences: An algorithm.

Vikas Kumar Maurya, Madhumathi Sanjeevi, Chandrasekar Narayanan Rahul, Ajitha Mohan, Dhanalakshmi Ramachandran, Rashmi Siddalingappa, Roshan Rauniyar, Sekar Kanagaraj

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Article in Journal of biosciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Vikas Kumar MauryaDepartment of Computational and Data Sciences, Indian Institute of Science, Bengaluru 560 012, India.
Madhumathi Sanjeevi
Chandrasekar Narayanan Rahul
Ajitha Mohan
Dhanalakshmi Ramachandran
Rashmi Siddalingappa
Roshan Rauniyar
Sekar Kanagaraj

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In recent years, several experimental evidences suggest that amino acid repeats are closely linked to many disease conditions, as they have a significant role in evolution of disordered regions of the polypeptide segments. Even though many algorithms and databases were developed for such analysis, each algorithm has some caveats, like limitation on the number of amino acids within the repeat patterns and number of query protein sequences. To this end, in the present work, a new method called the internal sequence repeats across multiple protein sequences (ISRMPS) is proposed for the first time to identify identical repeats across multiple protein sequences. It also identifies distantly located repeat patterns in various protein sequences. Our method can be applied to study evolutionary relationships, epitope mapping, CRISPR-Cas sequencing methods, and other comparative analytical assessments of protein sequences.

Indexed as

AlgorithmsAmino AcidsAmino Acid SequenceDatabases, FactualAmino Acids

Identifiers

PMID38445556

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.