雜志介紹

Biodata Mining雜志介紹

《Biodata Mining》是一本以English為主的開放獲取國際優秀期刊，中文名稱生物數據挖掘，本刊主要出版、報道生物學-MATHEMATICAL & COMPUTATIONAL BIOLOGY領域的研究動態以及在該領域取得的各方面的經驗和科研成果，介紹該領域有關本專業的最新進展，探討行業發展的思路和方法，以促進學術信息交流，提高行業發展。該刊已被國際權威數據庫SCIE收錄，為該領域相關學科的發展起到了良好的推動作用，也得到了本專業人員的廣泛認可。該刊最新影響因子為4，最新CiteScore 指數為7.9。

本刊近期中國學者發表的論文主要有：

• Motif mining based on network space compression

  Author: Qiang Zhang, Yuan Xu

• An iteration normalization and test method for differential expression analysis of RNA-seq data

  Author: Yan Zhou, Nan Lin, Baoxue Zhang

• Prediction of protein solvent accessibility using PSO-SVR with multiple sequence-derived features and weighted sliding window scheme

  Author: Jian Zhang, Wenhan Chen, Pingping Sun, Xiaowei Zhao, Zhiqiang Ma

• Mining causal relationships among clinical variables for cancer diagnosis based on Bayesian analysis

  Author: LiMin Wang

英文介紹

Biodata Mining雜志英文介紹

BioData Mining is an open access, open peer-reviewed journal encompassing research on all aspects of data mining applied to high-dimensional biological and biomedical data, focusing on computational aspects of knowledge discovery from large-scale genetic, transcriptomic, genomic, proteomic, and metabolomic data.

Topical areas include, but are not limited to:

-Development, evaluation, and application of novel data mining and machine learning algorithms.

-Adaptation, evaluation, and application of traditional data mining and machine learning algorithms.

-Open-source software for the application of data mining and machine learning algorithms.

-Design, development and integration of databases, software and web services for the storage, management, retrieval, and analysis of data from large scale studies.

-Pre-processing, post-processing, modeling, and interpretation of data mining and machine learning results for biological interpretation and knowledge discovery.