期刊簡介預計審稿時間： 23 Weeks

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.

BioData Mining 是一本開放獲取、開放的同行評審期刊，涵蓋了應用于高維生物和生物醫(yī)學數(shù)據(jù)的數(shù)據(jù)挖掘的各個方面的研究，重點研究從大規(guī)模遺傳、轉錄組、基因組、蛋白質(zhì)組和代謝組數(shù)據(jù)中發(fā)現(xiàn)知識的計算方面。

主題領域包括但不限于：

-新型數(shù)據(jù)挖掘和機器學習算法的開發(fā)、評估和應用。

-傳統(tǒng)數(shù)據(jù)挖掘和機器學習算法的調(diào)整、評估和應用。

-用于數(shù)據(jù)挖掘和機器學習算法應用的開源軟件。

-設計、開發(fā)和集成數(shù)據(jù)庫、軟件和 Web 服務，用于存儲、管理、檢索和分析來自大規(guī)模研究的數(shù)據(jù)。

-數(shù)據(jù)挖掘和機器學習結果的預處理、后處理、建模和解釋，用于生物解釋和知識發(fā)現(xiàn)。

《Biodata Mining》(生物數(shù)據(jù)挖掘)編輯部通訊方式為CAMPUS, 4 CRINAN ST, LONDON, ENGLAND, N1 9XW。如果您需要協(xié)助投稿或潤稿服務，您可以咨詢我們的客服老師。我們專注于期刊投稿服務十年，熟悉發(fā)表政策，可為您提供一對一投稿指導，避免您在投稿時頻繁碰壁，節(jié)省您的寶貴時間，有效提升發(fā)表機率，確保SCI檢索（檢索不了全額退款）。我們視信譽為生命，多方面確保文章安全保密，在任何情況下都不會泄露您的個人信息或稿件內(nèi)容。