Benchmarking Datasets in Bioinformatics, 2nd Volume

A special issue of Data (ISSN 2306-5729). This special issue belongs to the section "Computational Biology, Bioinformatics, and Biomedical Data Science".

Deadline for manuscript submissions: closed (20 November 2024) | Viewed by 583

Special Issue Editor

Special Issue Information

Dear Colleagues,

Over the last few years, computational predictions and identifications have gained importance in modern life science and medical science. Many efforts have been made to develop algorithms and computational models that can be used to identify molecular structures, functions, interactions, evolutions, and their relationships with complex disorders. To validate these methods, many benchmarking datasets have been constructed, applied, and released to the public domain. These benchmarking datasets form the basis of the fair comparison and validation of computational methods. A thorough discussion and comparison of these datasets is necessary. In this Special Issue, we aim to provide deep insights into the construction procedures and characteristics of different benchmarking datasets with the same, or similar, biological topics.

We are looking for manuscripts that discuss different benchmarking datasets which cover a single bioinformatics topic or a specific category of topics. These manuscripts can discuss and compare the construction procedures, data sources, and statistics of different datasets, as well as the computational methods that are developed and evaluated using these datasets. There is no limit or fixed boundary to these comparisons. All kinds of discussions, comments, and comparisons are welcome. In particular, a collection of different datasets covering a single topic or similar topics are welcome, as this will facilitate the further development of different computational methods. In general, all contributions related to bioinformatics benchmarking datasets may be included in this Special Issue.

Dr. Pufeng Du
Guest Editor

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Keywords

  • bioinformatics datasets
  • dataset construction
  • dataset comparisons
  • dataset qualities
  • dataset comments
  • dataset collections
  • comparison of computational methods based on datasets

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