雜志介紹

Patterns雜志介紹

《Patterns》是一本以English為主的開放獲取國際優(yōu)秀期刊，中文名稱模式，本刊主要出版、報道領(lǐng)域的研究動態(tài)以及在該領(lǐng)域取得的各方面的經(jīng)驗和科研成果，介紹該領(lǐng)域有關(guān)本專業(yè)的最新進展，探討行業(yè)發(fā)展的思路和方法，以促進學(xué)術(shù)信息交流，提高行業(yè)發(fā)展。該刊已被國際權(quán)威數(shù)據(jù)庫SCIE收錄，為該領(lǐng)域相關(guān)學(xué)科的發(fā)展起到了良好的推動作用，也得到了本專業(yè)人員的廣泛認(rèn)可。該刊最新影響因子為6.7，最新CiteScore 指數(shù)為10.6。

本刊近期中國學(xué)者發(fā)表的論文主要有：

• Self-supervised graph representation learning integrates multiple molecular networks and decodes gene-disease relationships

  Author: Wang, Yi; Sun, Zijun; He, Qiushun; Li, Jiwei; Ni, Ming; Yang, Meng

• Enhanced metagenomic deep learning for disease prediction and consistent signature recognition by restructured microbiome 2D representations

  Author: Shen, Wan Xiang; Liang, Shu Ran; Jiang, Yu Yang; Chen, Yu Zong

• Continuous diagnosis and prognosis by controlling the update process of deep neural networks

  Author: Sun, Chenxi; Li, Hongyan; Song, Moxian; Cai, Derun; Zhang, Baofeng; Hong, Shenda

• TriNet: A tri-fusion neural network for the prediction of anticancer and antimicrobial peptides

  Author: Zhou, Wanyun; Liu, Yufei; Li, Yingxin; Kong, Siqi; Wang, Weilin; Ding, Boyun; Han, Jiyun; Mou, Chaozhou; Gao, Xin; Liu, Juntao

英文介紹

Patterns雜志英文介紹

Patterns is a high-quality open access journal published by Cell Press, which publishes groundbreaking original research in various fields of data science. We are committed to sharing data science solutions for cross disciplinary problems. Patterns cover a wide global audience, including computer scientists, researchers in data intensive fields, data administrators, and policy makers. We adhere to the principle of fairness, ensuring that the data, software, workflows, algorithms, and other research results we publish are searchable, accessible, interoperable, and reusable. Patterns are the home of data scientists and researchers in both academic and industrial data intensive fields. This journal shares data science solutions from various disciplines, including computational science, physical science, life sciences, social sciences, and humanities.