Biodata Mining

杂志介绍

Biodata Mining杂志介绍

《Biodata Mining》是一本以English为主的开放获取国际优秀期刊，中文名称生物数据挖掘，本刊主要出版、报道生物学-MATHEMATICAL & COMPUTATIONAL BIOLOGY领域的研究动态以及在该领域取得的各方面的经验和科研成果，介绍该领域有关本专业的最新进展，探讨行业发展的思路和方法，以促进学术信息交流，提高行业发展。该刊已被国际权威数据库SCIE收录，为该领域相关学科的发展起到了良好的推动作用，也得到了本专业人员的广泛认可。该刊最新影响因子为4，最新CiteScore 指数为7.9。

本刊近期中国学者发表的论文主要有：

• 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

英文介绍

Biodata Mining杂志英文介绍

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.