Literature DB >> 28392341

Computational complexity of algorithms for sequence comparison, short-read assembly and genome alignment.

Shakuntala Baichoo1, Christos A Ouzounis2.   

Abstract

A multitude of algorithms for sequence comparison, short-read assembly and whole-genome alignment have been developed in the general context of molecular biology, to support technology development for high-throughput sequencing, numerous applications in genome biology and fundamental research on comparative genomics. The computational complexity of these algorithms has been previously reported in original research papers, yet this often neglected property has not been reviewed previously in a systematic manner and for a wider audience. We provide a review of space and time complexity of key sequence analysis algorithms and highlight their properties in a comprehensive manner, in order to identify potential opportunities for further research in algorithm or data structure optimization. The complexity aspect is poised to become pivotal as we will be facing challenges related to the continuous increase of genomic data on unprecedented scales and complexity in the foreseeable future, when robust biological simulation at the cell level and above becomes a reality.
Copyright © 2017 Elsevier B.V. All rights reserved.

Keywords:  Bioinformatics algorithms; Computational complexity; Genome alignment; Sequence comparison; Short-read assembly

Mesh:

Year:  2017        PMID: 28392341     DOI: 10.1016/j.biosystems.2017.03.003

Source DB:  PubMed          Journal:  Biosystems        ISSN: 0303-2647            Impact factor:   1.973


  5 in total

1.  Developing computational biology at meridian 23° E, and a little eastwards.

Authors:  Christos A Ouzounis
Journal:  J Biol Res (Thessalon)       Date:  2018-11-14       Impact factor: 1.889

2.  Athena: Automated Tuning of k-mer based Genomic Error Correction Algorithms using Language Models.

Authors:  Mustafa Abdallah; Ashraf Mahgoub; Hany Ahmed; Somali Chaterji
Journal:  Sci Rep       Date:  2019-11-06       Impact factor: 4.379

3.  Lerna: transformer architectures for configuring error correction tools for short- and long-read genome sequencing.

Authors:  Atul Sharma; Pranjal Jain; Ashraf Mahgoub; Zihan Zhou; Kanak Mahadik; Somali Chaterji
Journal:  BMC Bioinformatics       Date:  2022-01-06       Impact factor: 3.169

Review 4.  Technology dictates algorithms: recent developments in read alignment.

Authors:  Mohammed Alser; Jeremy Rotman; Onur Mutlu; Serghei Mangul; Dhrithi Deshpande; Kodi Taraszka; Huwenbo Shi; Pelin Icer Baykal; Harry Taegyun Yang; Victor Xue; Sergey Knyazev; Benjamin D Singer; Brunilda Balliu; David Koslicki; Pavel Skums; Alex Zelikovsky; Can Alkan
Journal:  Genome Biol       Date:  2021-08-26       Impact factor: 13.583

Review 5.  How Machine Learning and Statistical Models Advance Molecular Diagnostics of Rare Disorders Via Analysis of RNA Sequencing Data.

Authors:  Lea D Schlieben; Holger Prokisch; Vicente A Yépez
Journal:  Front Mol Biosci       Date:  2021-06-01
  5 in total

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