会议信息

ISMB 2026: International Conference on Intelligent Systems for Molecular Biology

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截稿日期:
2026-04-09 已截稿
通知日期:
2026-05-05
会议日期:
2026-07-12
会议地点:
Washington DC, USA
届数:
34
CCF: B   ICORE: A   QUALIS: A1   浏览: 49806   关注: 15   参加: 2
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ISMB
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会伴指数 (CP-I)

87.9 / 100
全站第 107 名 / 共 5,770 个会议 · 前 2%

生物信息学与健康信息学 第 2 / 184 人工智能与机器学习 第 16 / 755

学术认可 (35%)
100
投稿选择性 (20%)
93
会议传承 (20%)
96
社区关注 (10%)
53
资料公开度 (15%)
65

用到的输入: 收录等级：CCF B, ICORE A, QUALIS A1 · 录用率：17.6%（有记录的 5 届的均值） · 有据可查的届次：34 · 在会伴关注它的研究者：15 人 · 过去 24 个月打开过本页的研究者：33 人

公开资料里还缺: 历届信息 (+3.0) · 最佳论文记录 (+2.3)
主办方认领本会议后，可直接在这一页补上；分数每晚重算。如何提升这个分数

置信度 100% —— 分数中有多大比例来自实际观测到的数据，而不是中性基准。 这个分数是怎么算出来的 · 查看完整榜单 · 算法版本 1.2 · 算于 2026-11-07

征稿

ISMB 2026 (International Conference on Intelligent Systems for Molecular Biology) is a CCF B / ICORE A / QUALIS A1 conference held in Washington DC, USA on 2026-07-12. The paper submission deadline is 2026-04-09 (extended). Acceptance notifications are sent on 2026-05-05.

Topics Bioinformatics Education and Citizen Science (COSIs within this area include: Education) Systematic examination and analysis of learning models, outcomes, and educational programs. Serious gaming and game-ification. Bioinformatics of Microbes and Microbiomes (COSIs within this area include: BioVis, CAMDA, HiTSeq, MICROBIOME, MLCSB, NetBio, Text Mining) Computational methods and algorithms for studying microbial organisms, viruses, and their communities from omics and marker data. Biomedical Informatics (COSIs within this area include: Bio-Ontologies, BioVis, CAMDA, Function, HiTSeq, iRNA, MLCSB, NetBio, Text Mining, TransMed, VarI) Computational approaches to clinical and medical problems, including disease predisposition, diagnostic, progression, and treatment. Pharmacogenomics. Equity and Diversity in Computational Biology Research (Of interest to all COSIs) Research that examines issues of equity, representation, diversity, or other elements related to datasets, methods, or the field at large; health policy; fairness in ML; biases in GWAS studies; bias in literature; biology/genomics of traditionally understudied groups. Evolutionary, Comparative and Population Genomics (COSIs within this area include: BioVis, Evolution and Comparative Genomics, Function, HiTSeq, iRNA, MICROBIOME, MLCSB, VarI) Phylogeny estimation, and modelling variation and change under the influence of evolutionary processes. Selection and adaptation. Multi-species analyses. Genome Sequence Analysis (COSIs within this area include: BioVis, Evolution and Comparative Genomics, Function, HiTSeq, iRNA, MICROBIOME, MLCSB, NetBio, RegSys, TransMed, VarI) Assembly and mapping algorithms. Gene prediction and annotation. Detection, qualification, and annotation of genomic variants and their structural and functional effects. Macromolecular Sequence, Structure, and Function (COSIs within this area include: 3DSIG, Bio-Ontologies, BioVis, CompMS, Evolution and Comparative Genomics, Function, iRNA, MLCSB, RegSys, VarI) Analysis and annotation of DNA, RNA, and proteins to predict, characterize, and understand their structure, function, and evolution. Includes protein design and imaging techniques for macromolecules. Privacy and Security for Computational Biology (COSIs within this area include: HiTSeq, MLCSB, TransMed) Methods related to the protection of individualized molecular and medical information; privacy models; federated learning; GWAS on summary statistics; federated EHR data analysis; new approaches to federated data storage, access, and analysis. Regulatory and Functional Genomics (COSIs within this area include: Bio-Ontologies, BioVis, Evolution and Comparative Genomics, Function, HiTSeq, iRNA, MICROBIOME, MLCSB, NetBio, RegSys) Transcriptomics, single-cell RNA techniques, non-coding RNA, epigenetics, chromatin structure. Systems Biology and Networks (COSIs within this area include: Bio-Ontologies, BioVis, CompMS, Function, MICROBIOME, MLCSB, NetBio, RegSys, Text Mining, TransMed) Emergent properties and complex multi-component interactions within biological systems, considering genomic, proteomic, metabolomic, and other -omic data; gene regulation and circuit design. General Computational Biology Novel techniques in emerging areas of computational biology not covered by the other areas listed above, including intersections with other fields. You are encouraged to submit to one of the other thematic areas. If you feel your contribution is at the intersection of many fields, please pick one. If you still want to submit to this area, you will be asked to explain why. Please note that the submissions in this area and others are likely to be moved, subject to the chairs’ considerations.
由 Dou Sun 最后更新于

录用率

平均录用率: 17.6% 5 年间 (2007–2015).

年份提交数录用数录用率(%)
20152414217.4%
20132334017.2%
20112584818.6%
20092424619%
20074176615.8%

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