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Nature Computational Science

Nature Computational Science

SCIE

国际简称:NAT COMPUT SCI  参考译名:自然计算科学

  • 中科院分区

    1区

  • CiteScore分区

    Q1

  • JCR分区

    Q1

基本信息:
ISSN:2662-8457
是否OA:混合
是否预警:否
TOP期刊:是
出版信息:
出版商:Springer Nature
研究方向:Multiple
评价信息:
影响因子:20.3
CiteScore指数:25.4
SJR指数:4.252
SNIP指数:4.056
发文数据:
Gold OA文章占比:29.75%
研究类文章占比:87.23%
年发文量:94
英文简介 期刊介绍 CiteScore数据 中科院SCI分区 JCR分区 发文数据 常见问题

英文简介Nature Computational Science期刊介绍

The main goal of Nature Computational Science is to promote innovative applications of computing technology in various scientific fields, including but not limited to bioinformatics, chemical informatics, geographic informatics, computational physics, cosmology, materials science, and urban science. The content published in the journal covers both fundamental and applied research, including breakthrough algorithms, tools, and frameworks, as well as new insights and solutions to challenging real-world problems discovered through innovative ways of utilizing computing power.

As an online only journal, Nature Computational Science is able to quickly respond to the latest developments in the scientific community, enabling research results to be shared with global readers at the fastest speed possible. At the same time, the journal also provides readers with accurate and timely background information on the latest developments in the field of computational science by publishing comments, viewpoints, and news and opinion articles, promoting communication and discussion in the academic community.

期刊简介Nature Computational Science期刊介绍

《Nature Computational Science》是一本计算机科学优秀杂志。致力于发表原创科学研究结果,并为计算机科学各个领域的原创研究提供一个展示平台,以促进计算机科学领域的的进步。该刊鼓励先进的、清晰的阐述,从广泛的视角提供当前感兴趣的研究主题的新见解,或审查多年来某个重要领域的所有重要发展。该期刊特色在于及时报道计算机科学领域的最新进展和新发现新突破等。该刊近一年未被列入预警期刊名单,目前已被权威数据库SCIE收录,得到了广泛的认可。

该期刊投稿重要关注点:

Cite Score数据(2026年6月最新版)Nature Computational Science Cite Score数据

  • CiteScore:25.4
  • SJR:4.252
  • SNIP:4.056
学科类别 分区 排名 百分位
大类:Computer Science 小类:Computer Networks and Communications Q1 7 / 568

98%

大类:Computer Science 小类:Computer Science (miscellaneous) Q1 3 / 179

98%

大类:Computer Science 小类:Computer Science Applications Q1 18 / 1022

98%

CiteScore 是由Elsevier(爱思唯尔)推出的另一种评价期刊影响力的文献计量指标。反映出一家期刊近期发表论文的年篇均引用次数。CiteScore以Scopus数据库中收集的引文为基础,针对的是前四年发表的论文的引文。CiteScore的意义在于,它可以为学术界提供一种新的、更全面、更客观地评价期刊影响力的方法,而不仅仅是通过影响因子(IF)这一单一指标来评价。

历年Cite Score趋势图

中科院SCI分区Nature Computational Science 中科院分区

《新锐期刊分区表》(2026年3月发布) 综述期刊:否 Top期刊:是
大类学科 分区 小类学科 分区
计算机科学 1区 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS 计算机:跨学科应用 COMPUTER SCIENCE, THEORY & METHODS 计算机:理论方法 MULTIDISCIPLINARY SCIENCES 综合性期刊 1区 1区 1区
期刊分区表(2025年3月升级版) 综述期刊:否 Top期刊:是
大类学科 分区 小类学科 分区
计算机科学 1区 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS 计算机:跨学科应用 COMPUTER SCIENCE, THEORY & METHODS 计算机:理论方法 MULTIDISCIPLINARY SCIENCES 综合性期刊 1区 1区 1区

中科院分区表 是以客观数据为基础,运用科学计量学方法对国际、国内学术期刊依据影响力进行等级划分的期刊评价标准。它为我国科研、教育机构的管理人员、科研工作者提供了一份评价国际学术期刊影响力的参考数据,得到了全国各地高校、科研机构的广泛认可。

中科院分区表 将所有期刊按照一定指标划分为1区、2区、3区、4区四个层次,类似于“优、良、及格”等。最开始,这个分区只是为了方便图书管理及图书情报领域的研究和期刊评估。之后中科院分区逐步发展成为了一种评价学术期刊质量的重要工具。

历年中科院分区趋势图

JCR分区Nature Computational Science JCR分区

2025-2026年最新版
按JCI指标学科分区 收录子集 分区 排名 百分位
学科:COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS SCIE Q1 3 / 185

98.6

学科:COMPUTER SCIENCE, THEORY & METHODS SCIE Q1 2 / 146

99

学科:MULTIDISCIPLINARY SCIENCES SCIE Q1 7 / 140

95.4

学科:COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS SCIE Q1 4 / 185

98.11

学科:COMPUTER SCIENCE, THEORY & METHODS SCIE Q1 2 / 147

98.98

学科:MULTIDISCIPLINARY SCIENCES SCIE Q1 6 / 140

96.07

2023-2024年最新版
按JCI指标学科分区 收录子集 分区 排名 百分位
学科:COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS ESCI Q1 2 / 169

99.1

学科:COMPUTER SCIENCE, THEORY & METHODS ESCI Q1 4 / 143

97.6

学科:MULTIDISCIPLINARY SCIENCES ESCI Q1 9 / 134

93.7

学科:COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS ESCI Q1 5 / 169

97.34

学科:COMPUTER SCIENCE, THEORY & METHODS ESCI Q1 5 / 143

96.85

学科:MULTIDISCIPLINARY SCIENCES ESCI Q1 11 / 135

92.22

JCR分区的优势在于它可以帮助读者对学术文献质量进行评估。不同学科的文章引用量可能存在较大的差异,此时单独依靠影响因子(IF)评价期刊的质量可能是存在一定问题的。因此,JCR将期刊按照学科门类和影响因子分为不同的分区,这样读者可以根据自己的研究领域和需求选择合适的期刊。

历年影响因子趋势图

本刊中国学者近年发表论文

  • 1、HorusEye: a self-supervised foundation model for generalizable X-ray tomography restoratio

    Author: Chu, Yuetan; Zhou, Longxi; Luo, Gongning; Kang, Kai; Dong, Suyu; Han, Zhongyi; Wu, Lianming; Meng, Xianglin; Yang, Changchun; Guo, Xin; Cheng, Yuan; Qi, Yuan; Liu, Xin; Xie, Dexuan; Li, Yue; Henao, Ricardo; Xiao, Xigang; Cao, Shaodong; Setti, Gianluca; Qiu, Zhaowen; Gao, Xin

    Journal: NATURE COMPUTATIONAL SCIENCE. 2026; Vol. 6, Issue 4, pp. -. DOI: 10.1038/s43588-026-00973-3

  • 2、DualGPT-AB: a dual-stage generative optimization framework for therapeutic antibody desig

    Author: Xie, Dongna; Chen, Siyuan; Zeng, Xi; Lu, Dazhi; Jiao, Shaoqing; Xiao, Shuyuan; Liu, Jiaming; Hao, Jianye; Dai, Hui; Peng, Jiajie

    Journal: NATURE COMPUTATIONAL SCIENCE. 2026; Vol. , Issue , pp. -. DOI: 10.1038/s43588-026-00976-0

  • 3、Feature-preserving manifold approximation and projection to analyze single-cell dat

    Author: Yang, Yang; Gong, Jialei; Sun, Hongjian; Choo, Amos; Mar, Jessica Cara; Wei, Yunbo; Zhang, Yu; Zhang, Wenjie; Shu, Minglei; Tuong, Zewen Kelvin; Yu, Di

    Journal: NATURE COMPUTATIONAL SCIENCE. 2026; Vol. , Issue , pp. -. DOI: 10.1038/s43588-026-00970-6

  • 4、Self-optimized spectral distance for low-light high-throughput Raman hyperspectral imagin

    Author: Chen, Yurong; Wang, Shen; Wang, Yaonan; Mao, Jianxu; Liu, Lizhu; Cao, Xiaoxu; Chen, Zhuo; Zhang, Hui

    Journal: NATURE COMPUTATIONAL SCIENCE. 2026; Vol. , Issue , pp. -. DOI: 10.1038/s43588-026-00957-3

  • 5、Mapping the potential and limitations of using generative AI technologies to address socio-economic challenges in LMIC

    Author: Adams, Rachel; Adeleke, Fola; Junck, Leah; Alayande, Ayantola; Gupta, Aarushi; Aneja, Urvashi; Segun, Samuel; Parkes-Ratanshi, Rosalind; Abdella, Selam; Gaffley, Mark; Mahoney, Scott; Makamu, Rirhandzu; Eghele Adade, Nana; Bian, Liping; Kintu, Timothy; Mugume, Atwine; Germani, Aline; El Kawak, Michelle; Patel, Bheeshma; Lawa, Olanrewaju; Khalid, Sara; Adekanmbi, Olubayo; Sikiru, Rasheedat; Ogunremi, Toyib; Yusuf, Farhan; Minaye, Hanna; Etuk, Imo; Nsenga, Jimmy; Urs, Uma; Zaman, Marzia; Mamun, Khondaker A.; Resende, Vivian; Faria Silva Trocoli-Couto, Pedro Henrique; Zaimova, Rositsa; Alpha Diallo, Mamadou; Kofi Quakyi, Nana; Liu, Xiao Fan; Jjingo, Daudi; Elhajj, Imad; Nakatumba-Nabende, Joyce; Roman, Tamlyn Eslie; Mustafa, Maryam; Hendry, Brenda; Hooda, Yogesh; Anebelundu, Chinazo; Khanal, Bishesh; Sultan, Faisal; Ravi, Nirmal; Akogo, Darlington; Brey, Zameer; Cohen, Dave; Proctor, Joshua; Mohamedali, Essa; Mobisson, Nneka; Taylor, Amelia; Archegas, Joao; Mahale, Amrita; Lesh, Neal; Duncan, Enrica; Maginga, Theofrida J.; Morales, Hugo Manuel Paz; Pereira Dos Santos, Henrique Dias; Vo, Tue; Th Nguyen, Trang; Korom, Robert; Leventhal, Michael; Jain, Shashi; Maria De Oliveira Ciabati, Livia; Devarsetty, Praveen; Hirst, Jane; Sharma, Ankita; Chowdhury, Moinul; Araujo Lima, Henrique; Govathson, Caroline; Morris, Sarah

    Journal: NATURE COMPUTATIONAL SCIENCE. 2026; Vol. , Issue , pp. -. DOI: 10.1038/s43588-026-00960-8

  • 6、A neural network that bridges sensory experience and symbolic though

    Author: Chen, Yang; Bi, Yanchao

    Journal: NATURE COMPUTATIONAL SCIENCE. 2026; Vol. , Issue , pp. -. DOI: 10.1038/s43588-026-00968-0

  • 7、De novo design of functional nucleic acids of aptamer

    Author: Zhang, Zhiming; Jiang, Meng; He, Axin; Zhu, Youyuan; Wang, Ercheng; Wan, Liqi; Qiu, Jiezhong; Guo, Pei; Chen, Guangyong; Han, Da

    Journal: NATURE COMPUTATIONAL SCIENCE. 2026; Vol. , Issue , pp. -. DOI: 10.1038/s43588-026-00965-3

  • 8、BrainParc: unified lifespan brain parcellation from structural magnetic resonance image

    Author: Liu, Jiameng; Liu, Feihong; Sun, Kaicong; Cui, Zhiming; Sun, Tianyang; Cao, Zehong; Huang, Jiawei; Bai, Shuwei; Wang, Yulin; Dou, Yulong; Zhang, Kaicheng; Jiang, Caiwen; Ge, Yuyan; Zhang, Han; Shi, Feng; Shen, Dinggang

    Journal: NATURE COMPUTATIONAL SCIENCE. 2026; Vol. , Issue , pp. -. DOI: 10.1038/s43588-026-00963-5

投稿常见问题