These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
158 related articles for article (PubMed ID: 30334214)
1. Selection of Informative Examples in Chemogenomic Datasets. Reker D; Brown JB Methods Mol Biol; 2018; 1825():369-410. PubMed ID: 30334214 [TBL] [Abstract][Full Text] [Related]
2. Linear and Kernel Model Construction Methods for Predicting Drug-Target Interactions in a Chemogenomic Framework. Yamanishi Y Methods Mol Biol; 2018; 1825():355-368. PubMed ID: 30334213 [TBL] [Abstract][Full Text] [Related]
3. Active learning for computational chemogenomics. Reker D; Schneider P; Schneider G; Brown JB Future Med Chem; 2017 Mar; 9(4):381-402. PubMed ID: 28263088 [TBL] [Abstract][Full Text] [Related]
4. Ask the experts: computational chemistry. Matta CF; Hutter MC Future Med Chem; 2018 Jul; 10(13):1521-1524. PubMed ID: 29992825 [No Abstract] [Full Text] [Related]
5. Drug Target Identification with Machine Learning: How to Choose Negative Examples. Najm M; Azencott CA; Playe B; Stoven V Int J Mol Sci; 2021 May; 22(10):. PubMed ID: 34066072 [TBL] [Abstract][Full Text] [Related]
6. A Machine Learning Approach for Drug-target Interaction Prediction using Wrapper Feature Selection and Class Balancing. Redkar S; Mondal S; Joseph A; Hareesha KS Mol Inform; 2020 May; 39(5):e1900062. PubMed ID: 32003548 [TBL] [Abstract][Full Text] [Related]
7. A big data approach with artificial neural network and molecular similarity for chemical data mining and endocrine disruption prediction. Paulose R; Jegatheesan K; Balakrishnan GS Indian J Pharmacol; 2018; 50(4):169-176. PubMed ID: 30505052 [TBL] [Abstract][Full Text] [Related]
8. TargetHunter: an in silico target identification tool for predicting therapeutic potential of small organic molecules based on chemogenomic database. Wang L; Ma C; Wipf P; Liu H; Su W; Xie XQ AAPS J; 2013 Apr; 15(2):395-406. PubMed ID: 23292636 [TBL] [Abstract][Full Text] [Related]
10. Data Mining and Computational Modeling of High-Throughput Screening Datasets. Ekins S; Clark AM; Dole K; Gregory K; Mcnutt AM; Spektor AC; Weatherall C; Litterman NK; Bunin BA Methods Mol Biol; 2018; 1755():197-221. PubMed ID: 29671272 [TBL] [Abstract][Full Text] [Related]
11. Applicability Domain of Active Learning in Chemical Probe Identification: Convergence in Learning from Non-Specific Compounds and Decision Rule Clarification. Polash AH; Nakano T; Takeda S; Brown JB Molecules; 2019 Jul; 24(15):. PubMed ID: 31357419 [TBL] [Abstract][Full Text] [Related]
12. An efficient data preprocessing approach for large scale medical data mining. Hu YH; Lin WC; Tsai CF; Ke SW; Chen CW Technol Health Care; 2015; 23(2):153-60. PubMed ID: 25515050 [TBL] [Abstract][Full Text] [Related]
13. Global optimization-based inference of chemogenomic features from drug-target interactions. Zu S; Chen T; Li S Bioinformatics; 2015 Aug; 31(15):2523-9. PubMed ID: 25819672 [TBL] [Abstract][Full Text] [Related]
14. Fundamental Bioinformatic and Chemoinformatic Data Processing. Brown JB Methods Mol Biol; 2018; 1825():95-129. PubMed ID: 30334204 [TBL] [Abstract][Full Text] [Related]
15. The opportunities of mining historical and collective data in drug discovery. Wassermann AM; Lounkine E; Davies JW; Glick M; Camargo LM Drug Discov Today; 2015 Apr; 20(4):422-34. PubMed ID: 25463034 [TBL] [Abstract][Full Text] [Related]
16. Identifying Drug-Target Interactions with Decision Templates. Yan XY; Zhang SW Curr Protein Pept Sci; 2018; 19(5):498-506. PubMed ID: 27829344 [TBL] [Abstract][Full Text] [Related]