Methods In Computational Genomics

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87

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15

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Methods In Computational Genomics

25.2K

views

87

authors

15

articles

Editorial

25 January 2024

Editorial: Methods in computational genomics

Lei Chen

and

Nathan D. Olson

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Editors

2

Nathan Olson

National Institute of Standards and Technology (NIST)

Lei Chen

Shanghai Maritime University

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About

This Research Topic is part of the Methods in Genetics series.

This series aims to highlight the latest experimental techniques and methods used to investigate fundamental questions in Computational Genomics research, from computational analysis of large multidimensional numeric datasets, prediction of the function of novel domains, motifs, genes and proteins using omics data to algorithms which provide meaningful insights into biology from the analysis of genomic data.

Review articles or opinions on methodologies or applications including the advantages and limitations of each are welcome. This Topic includes technologies and up-to-date methods which help advance science.

The contributions to this collection will undergo peer-review. Novelty may vary, but the utility of a method or protocol must be evident. We welcome contributions covering all aspects of computational genomics.

This Research Topic welcomes:

• Methods: Describing either new or existing methods that are significantly improved or adapted for specific purposes. These manuscripts may include primary (original) data.

• Protocols: Detailed descriptions, including pitfalls and troubleshooting, to benefit those who may evaluate or employ the techniques. The protocols must be proven to work.

• Perspective or General Commentaries.

• Reviews and mini-reviews of topical methods and protocols highlighting the important future directions of the field.

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Editors

Nathan Olson

National Institute of Standards and Technology (NIST)

Lei Chen

Shanghai Maritime University

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Published In

Frontiers in Genetics

Computational Genomics

Frontiers in Plant Science

Computational Genomics

Frontiers in Bioengineering and Biotechnology

Computational Genomics

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