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In silicotoxicology: comprehensive benchmarking of multi‐label classification methods applied to chemical toxicity data
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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Introduction to Data Mining in Bioinformatics
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Pattern Recognition in Bioinformatics : 5th IAPR International Conference, PRIB 2010, Nijmegen, The Netherlands, September 22-24, 2010. Proceedings
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FDA's Priority-Based Assessment of Food Additives
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FDA's Priority-Based Assessment of Food Additives
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The future of toxicity testing: a focus on in vitro methods using a quantitative high-throughput screening platform
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An analysis of genetic toxicity, reproductive and developmental toxicity, and carcinogenicity data: II. Identification of genotoxicants, reprotoxicants, and carcinogens using in silico methods
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Multi-label classification using boolean matrix decomposition
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Predicting Chemical Toxicity Effects Based on Chemical-Chemical Interactions
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Computational prediction of toxicity
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Prediction of Human Population Responses to Toxic Compounds by a Collaborative Competition
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DeepTox: Toxicity Prediction using Deep Learning
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SUBTILISIN AN EMINENT MICROBIAL PRODUCT AS A POTENTIAL SKIN CARE REGULATOR OF MELANOGENESIS –A PARADIGM SYNCHRONIZED WITH IN VITRO / IN SILICO APPROACH
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