Suppr超能文献

相似文献

1
Predicting mechanism of action of cellular perturbations with pathway activity signatures.
Bioinformatics. 2020 Sep 15;36(18):4781-4788. doi: 10.1093/bioinformatics/btaa590.
2
Predicting mechanism of action of novel compounds using compound structure and transcriptomic signature coembedding.
Bioinformatics. 2021 Jul 12;37(Suppl_1):i376-i382. doi: 10.1093/bioinformatics/btab275.
3
Open MoA: revealing the mechanism of action (MoA) based on network topology and hierarchy.
Bioinformatics. 2023 Nov 1;39(11). doi: 10.1093/bioinformatics/btad666.
4
Screening novel drug candidates for Alzheimer's disease by an integrated network and transcriptome analysis.
Bioinformatics. 2020 Nov 1;36(17):4626-4632. doi: 10.1093/bioinformatics/btaa563.
5
Comparative Network Reconstruction using mixed integer programming.
Bioinformatics. 2018 Sep 1;34(17):i997-i1004. doi: 10.1093/bioinformatics/bty616.
6
ndexr-an R package to interface with the network data exchange.
Bioinformatics. 2018 Feb 15;34(4):716-717. doi: 10.1093/bioinformatics/btx683.
7
PathWalks: identifying pathway communities using a disease-related map of integrated information.
Bioinformatics. 2020 Jul 1;36(13):4070-4079. doi: 10.1093/bioinformatics/btaa291.
8
Inferring perturbation profiles of cancer samples.
Bioinformatics. 2021 Aug 25;37(16):2441-2449. doi: 10.1093/bioinformatics/btab113.
9
corto: a lightweight R package for gene network inference and master regulator analysis.
Bioinformatics. 2020 Jun 1;36(12):3916-3917. doi: 10.1093/bioinformatics/btaa223.
10
Learning signaling networks from combinatorial perturbations by exploiting siRNA off-target effects.
Bioinformatics. 2019 Jul 15;35(14):i605-i614. doi: 10.1093/bioinformatics/btz334.

引用本文的文献

1
Guiding Drug Repositioning for Cancers Based on Drug Similarity Networks.
Int J Mol Sci. 2023 Jan 23;24(3):2244. doi: 10.3390/ijms24032244.
2
Connecting omics signatures and revealing biological mechanisms with iLINCS.
Nat Commun. 2022 Aug 9;13(1):4678. doi: 10.1038/s41467-022-32205-3.
3
Chemical-induced gene expression ranking and its application to pancreatic cancer drug repurposing.
Patterns (N Y). 2022 Feb 4;3(4):100441. doi: 10.1016/j.patter.2022.100441. eCollection 2022 Apr 8.
4
Predicting mechanism of action of novel compounds using compound structure and transcriptomic signature coembedding.
Bioinformatics. 2021 Jul 12;37(Suppl_1):i376-i382. doi: 10.1093/bioinformatics/btab275.

本文引用的文献

1
Footprint-based functional analysis of multiomic data.
Curr Opin Syst Biol. 2019 Jun;15:82-90. doi: 10.1016/j.coisb.2019.04.002.
2
A Bayesian approach to accurate and robust signature detection on LINCS L1000 data.
Bioinformatics. 2020 May 1;36(9):2787-2795. doi: 10.1093/bioinformatics/btaa064.
3
From expression footprints to causal pathways: contextualizing large signaling networks with CARNIVAL.
NPJ Syst Biol Appl. 2019 Nov 11;5:40. doi: 10.1038/s41540-019-0118-z. eCollection 2019.
4
Influence of batch effect correction methods on drug induced differential gene expression profiles.
BMC Bioinformatics. 2019 Aug 22;20(1):437. doi: 10.1186/s12859-019-3028-6.
5
A Comparison of the TempO-Seq S1500+ Platform to RNA-Seq and Microarray Using Rat Liver Mode of Action Samples.
Front Genet. 2018 Oct 30;9:485. doi: 10.3389/fgene.2018.00485. eCollection 2018.
6
L1000FWD: fireworks visualization of drug-induced transcriptomic signatures.
Bioinformatics. 2018 Jun 15;34(12):2150-2152. doi: 10.1093/bioinformatics/bty060.
7
Perturbation-response genes reveal signaling footprints in cancer gene expression.
Nat Commun. 2018 Jan 2;9(1):20. doi: 10.1038/s41467-017-02391-6.
8
A Next Generation Connectivity Map: L1000 Platform and the First 1,000,000 Profiles.
Cell. 2017 Nov 30;171(6):1437-1452.e17. doi: 10.1016/j.cell.2017.10.049.
9
PLATE-Seq for genome-wide regulatory network analysis of high-throughput screens.
Nat Commun. 2017 Jul 24;8(1):105. doi: 10.1038/s41467-017-00136-z.
10
Network propagation: a universal amplifier of genetic associations.
Nat Rev Genet. 2017 Sep;18(9):551-562. doi: 10.1038/nrg.2017.38. Epub 2017 Jun 12.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验