相关参考文献
注意：仅列出部分参考文献，下载原文获取全部文献信息。6 Deep Learning in Drug Discovery
Erik Gawehn et al.
MOLECULAR INFORMATICS (2016)
A deep learning framework for modeling structural features of RNA-binding protein targets
Sai Zhang et al.
NUCLEIC ACIDS RESEARCH (2016)
A simple model predicts UGT-mediated metabolism
Na Le Dang et al.
BIOINFORMATICS (2016)
Applications of Deep Learning in Biomedicine
Polina Mamoshina et al.
MOLECULAR PHARMACEUTICS (2016)
Mastering the game of Go with deep neural networks and tree search
David Silver et al.
NATURE (2016)
Machine-learning-assisted materials discovery using failed experiments
Paul Raccuglia et al.
NATURE (2016)
Modeling Reactivity to Biological Macromolecules with a Deep Multitask Network
Tyler B. Hughes et al.
ACS CENTRAL SCIENCE (2016)
DeepTox: Toxicity Prediction using Deep Learning
Andreas Mayr et al.
FRONTIERS IN ENVIRONMENTAL SCIENCE (2016)
Identifying Biological Pathway Interrupting Toxins Using Multi-Tree Ensembles
Gergo Barta
FRONTIERS IN ENVIRONMENTAL SCIENCE (2016)
Consensus Modeling for HTS Assays Using In silico Descriptors Calculates the Best Balanced Accuracy in Tox21 Challenge
Ahmed Abdelaziz et al.
FRONTIERS IN ENVIRONMENTAL SCIENCE (2016)
Learning from the Harvard Clean Energy Project: The Use of Neural Networks to Accelerate Materials Discovery
Edward O. Pyzer-Knapp et al.
ADVANCED FUNCTIONAL MATERIALS (2015)
Site of Reactivity Models Predict Molecular Reactivity of Diverse Chemicals with Glutathione
Tyler B. Hughes et al.
CHEMICAL RESEARCH IN TOXICOLOGY (2015)
ImageNet Large Scale Visual Recognition Challenge
Olga Russakovsky et al.
INTERNATIONAL JOURNAL OF COMPUTER VISION (2015)
Fourier series of atomic radial distribution functions: A molecular fingerprint for machine learning models of quantum chemical properties
O. Anatole von Lilienfeld et al.
INTERNATIONAL JOURNAL OF QUANTUM CHEMISTRY (2015)
Crystal structure representations for machine learning models of formation energies
Felix Faber et al.
INTERNATIONAL JOURNAL OF QUANTUM CHEMISTRY (2015)
Improved Prediction of CYP-Mediated Metabolism with Chemical Fingerprints
Jed Zaretzki et al.
JOURNAL OF CHEMICAL INFORMATION AND MODELING (2015)
Deep Learning for Drug-Induced Liver Injury
Youjun Xu et al.
JOURNAL OF CHEMICAL INFORMATION AND MODELING (2015)
Deep Neural Nets as a Method for Quantitative Structure-Activity Relationships
Junshui Ma et al.
JOURNAL OF CHEMICAL INFORMATION AND MODELING (2015)
Machine Learning of Parameters for Accurate Semiempirical Quantum Chemical Calculations
Pavlo O. Dral et al.
JOURNAL OF CHEMICAL THEORY AND COMPUTATION (2015)
Big Data Meets Quantum Chemistry Approximations: The Δ-Machine Learning Approach
Raghunathan Ramakrishnan et al.
JOURNAL OF CHEMICAL THEORY AND COMPUTATION (2015)
Accurate Modeling of Ionic Surfactants at High Concentration
Garrett B. Goh et al.
JOURNAL OF PHYSICAL CHEMISTRY B (2015)
Predicting the sequence specificities of DNA- and RNA-binding proteins by deep learning
Babak Alipanahi et al.
NATURE BIOTECHNOLOGY (2015)
Big-deep-smart data in imaging for guiding materials design
Sergei V. Kalinin et al.
NATURE MATERIALS (2015)
Deep learning in neural networks: An overview
Juergen Schmidhuber
NEURAL NETWORKS (2015)
Artificial evolution of coumarin dyes for dye sensitized solar cells
Vishwesh Venkatraman et al.
PHYSICAL CHEMISTRY CHEMICAL PHYSICS (2015)
Accurate and efficient target prediction using a potency-sensitive influence-relevance voter
Alessandro Lusci et al.
JOURNAL OF CHEMINFORMATICS (2015)
Improving prediction of secondary structure, local backbone angles, and solvent accessible surface area of proteins by iterative deep learning
Rhys Heffernan et al.
SCIENTIFIC REPORTS (2015)
Modeling Epoxidation of Drug-like Molecules with a Deep Machine Learning Network
Tyler B. Hughes et al.
ACS CENTRAL SCIENCE (2015)
Predicting Backbone Cα Angles and Dihedrals from Protein Sequences by Stacked Sparse Auto-Encoder Deep Neural Network
James Lyons et al.
JOURNAL OF COMPUTATIONAL CHEMISTRY (2014)
Modeling electronic quantum transport with machine learning
Alejandro Lopez-Bezanilla et al.
PHYSICAL REVIEW B (2014)
Searching for exotic particles in high-energy physics with deep learning
P. Baldi et al.
NATURE COMMUNICATIONS (2014)
Profiling of the Tox21 10K compound library for agonists and antagonists of the estrogen receptor alpha signaling pathway
Ruili Huang et al.
SCIENTIFIC REPORTS (2014)
Stalking the Materials Genome: A Data-Driven Approach to the Virtual Design of Nanostructured Polymers
Curt M. Breneman et al.
ADVANCED FUNCTIONAL MATERIALS (2013)
Representation Learning: A Review and New Perspectives
Yoshua Bengio et al.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2013)
Deep Architectures and Deep Learning in Chemoinformatics: The Prediction of Aqueous Solubility for Drug-Like Molecules
Alessandro Lusci et al.
JOURNAL OF CHEMICAL INFORMATION AND MODELING (2013)
XenoSite: Accurately Predicting CYP-Mediated Sites of Metabolism with Neural Networks
Jed Zaretzki et al.
JOURNAL OF CHEMICAL INFORMATION AND MODELING (2013)
Lessons Learned in Empirical Scoring with smina from the CSAR 2011 Benchmarking Exercise
David Ryan Koes et al.
JOURNAL OF CHEMICAL INFORMATION AND MODELING (2013)
Assessment and Validation of Machine Learning Methods for Predicting Molecular Atomization Energies
Katja Hansen et al.
JOURNAL OF CHEMICAL THEORY AND COMPUTATION (2013)
CHARMM36 all-atom additive protein force field: Validation based on comparison to NMR data
Jing Huang et al.
JOURNAL OF COMPUTATIONAL CHEMISTRY (2013)
High-throughput sequencing for biology and medicine
Wendy Weijia Soon et al.
MOLECULAR SYSTEMS BIOLOGY (2013)
Evaluation of methods for modeling transcription factor sequence specificity
Matthew T. Weirauch et al.
NATURE BIOTECHNOLOGY (2013)
Machine learning of molecular electronic properties in chemical compound space
Gregoire Montavon et al.
NEW JOURNAL OF PHYSICS (2013)
Machine-learning approach for one- and two-body corrections to density functional theory: Applications to molecular and condensed water
Albert P. Bartok et al.
PHYSICAL REVIEW B (2013)
Commentary: The Materials Project: A materials genome approach to accelerating materials innovation
Anubhav Jain et al.
APL MATERIALS (2013)
Exploring Chemical Space for Drug Discovery Using the Chemical Universe Database
Jean-Louis Reymond et al.
ACS CHEMICAL NEUROSCIENCE (2012)
Deep architectures for protein contact map prediction
Pietro Di Lena et al.
BIOINFORMATICS (2012)
Predicting protein residue-residue contacts using deep networks and boosting
Jesse Eickholt et al.
BIOINFORMATICS (2012)
Quantitative Structure-Property Relationship Modeling of Diverse Materials Properties
Tu Le et al.
CHEMICAL REVIEWS (2012)
Are Protein Force Fields Getting Better? A Systematic Benchmark on 524 Diverse NMR Measurements
Kyle A. Beauchamp et al.
JOURNAL OF CHEMICAL THEORY AND COMPUTATION (2012)
SPINE X: Improving protein secondary structure prediction by multistep learning coupled with prediction of solvent accessible surface area and backbone torsion angles
Eshel Faraggi et al.
JOURNAL OF COMPUTATIONAL CHEMISTRY (2012)
Directory of Useful Decoys, Enhanced (DUD-E): Better Ligands and Decoys for Better Benchmarking
Michael M. Mysinger et al.
JOURNAL OF MEDICINAL CHEMISTRY (2012)
Protein structure prediction from sequence variation
Debora S. Marks et al.
NATURE BIOTECHNOLOGY (2012)
PubChem's BioAssay Database
Yanli Wang et al.
NUCLEIC ACIDS RESEARCH (2012)
Fast and Accurate Modeling of Molecular Atomization Energies with Machine Learning
Matthias Rupp et al.
PHYSICAL REVIEW LETTERS (2012)
Predicting residue-residue contacts using random forest models
Yunqi Li et al.
BIOINFORMATICS (2011)
A Kirkwood-Buff Derived Force Field for Aqueous Alkali Halides
Moon Bae Gee et al.
JOURNAL OF CHEMICAL THEORY AND COMPUTATION (2011)
PaDEL-Descriptor: An Open Source Software to Calculate Molecular Descriptors and Fingerprints
Chun Wei Yap
JOURNAL OF COMPUTATIONAL CHEMISTRY (2011)
Evaluation of residue-residue contact predictions in CASP9
Bohdan Monastyrskyy et al.
PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS (2011)
How Fast-Folding Proteins Fold
Kresten Lindorff-Larsen et al.
SCIENCE (2011)
Quantitative Nanostructure-Activity Relationship Modeling
Denis Fourches et al.
ACS NANO (2010)
Finding Nature's Missing Ternary Oxide Compounds Using Machine Learning and Density Functional Theory
Geoffroy Hautier et al.
CHEMISTRY OF MATERIALS (2010)
NWChem: A comprehensive and scalable open-source solution for large scale molecular simulations
M. Valiev et al.
COMPUTER PHYSICS COMMUNICATIONS (2010)
3D-QSAR in Drug Design - A Review
Jitender Verma et al.
CURRENT TOPICS IN MEDICINAL CHEMISTRY (2010)
Deep Machine Learning-A New Frontier in Artificial Intelligence Research
Itamar Arel et al.
IEEE COMPUTATIONAL INTELLIGENCE MAGAZINE (2010)
Extended-Connectivity Fingerprints
David Rogers et al.
JOURNAL OF CHEMICAL INFORMATION AND MODELING (2010)
Simulation of Osmotic Pressure in Concentrated Aqueous Salt Solutions
Yun Luo et al.
JOURNAL OF PHYSICAL CHEMISTRY LETTERS (2010)
Quantitative Structure-Fluorescence Property Relationship Analysis of a Large BODIPY Library
Andreas Schueller et al.
MOLECULAR INFORMATICS (2010)
Best Practices for QSAR Model Development, Validation, and Exploitation
Alexander Tropsha
MOLECULAR INFORMATICS (2010)
Using multi-data hidden Markov models trained on local neighborhoods of protein structure to predict residue-residue contacts
Patrik Bjorkholm et al.
BIOINFORMATICS (2009)
Support vector machines and its applications in chemistry
Hongdong Li et al.
CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS (2009)
Human drug hepatotoxicity: a contemporary clinical perspective
David N. Assis et al.
EXPERT OPINION ON DRUG METABOLISM & TOXICOLOGY (2009)
Influence Relevance Voting: An Accurate And Interpretable Virtual High Throughput Screening Method
S. Joshua Swamidass et al.
JOURNAL OF CHEMICAL INFORMATION AND MODELING (2009)
Maximum Unbiased Validation (MUV) Data Sets for Virtual Screening Based on PubChem Bioactivity Data
Sebastian G. Rohrer et al.
JOURNAL OF CHEMICAL INFORMATION AND MODELING (2009)
CHARMM: The Biomolecular Simulation Program
B. R. Brooks et al.
JOURNAL OF COMPUTATIONAL CHEMISTRY (2009)
Predicting Continuous Local Structure and the Effect of Its Substitution for Secondary Structure in Fragment-Free Protein Structure Prediction
Eshel Faraggi et al.
STRUCTURE (2009)
Progress and challenges in protein structure prediction
Yang Zhang
CURRENT OPINION IN STRUCTURAL BIOLOGY (2008)
Prediction of Fungicidal Activities of Rice Blast Disease Based on Least-Squares Support Vector Machines and Project Pursuit Regression
Hongying Du et al.
JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY (2008)
Mold2, molecular descriptors from 2D structures for chemoinformatics and toxicoinformatics
Huixiao Hong et al.
JOURNAL OF CHEMICAL INFORMATION AND MODELING (2008)
Accelerating density functional calculations with graphics processing unit
Koji Yasuda
JOURNAL OF CHEMICAL THEORY AND COMPUTATION (2008)
GROMACS 4: Algorithms for highly efficient, load-balanced, and scalable molecular simulation
Berk Hess et al.
JOURNAL OF CHEMICAL THEORY AND COMPUTATION (2008)
Consistent blind protein structure generation from NMR chemical shift data
Yang Shen et al.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2008)
Accelerating molecular modeling applications with graphics processors
John E. Stone et al.
JOURNAL OF COMPUTATIONAL CHEMISTRY (2007)
Principles of QSAR models validation: internal and external
Paola Gramatica
QSAR & COMBINATORIAL SCIENCE (2007)
Improved residue contact prediction using support vector machines and a large feature set
Jianlin Cheng et al.
BMC BIOINFORMATICS (2007)
Contact prediction using mutual information and neural nets
George Shackelford et al.
PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS (2007)
Statistical potential for assessment and prediction of protein structures
Min-Yi Shen et al.
PROTEIN SCIENCE (2006)
A fast learning algorithm for deep belief nets
Geoffrey E. Hinton et al.
NEURAL COMPUTATION (2006)
Physically realistic homology models built with ROSETTA can be more accurate than their templates
KMS Misura et al.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2006)
Predicting physical properties of ionic liquids
M Deetlefs et al.
PHYSICAL CHEMISTRY CHEMICAL PHYSICS (2006)
Advances in methods and algorithms in a modern quantum chemistry program package
Yihan Shao et al.
PHYSICAL CHEMISTRY CHEMICAL PHYSICS (2006)
Scalable molecular dynamics with NAMD
JC Phillips et al.
JOURNAL OF COMPUTATIONAL CHEMISTRY (2005)
The Amber biomolecular simulation programs
DA Case et al.
JOURNAL OF COMPUTATIONAL CHEMISTRY (2005)
PISCES: recent improvements to a PDB sequence culling server
GL Wang et al.
NUCLEIC ACIDS RESEARCH (2005)
PROFcon: novel prediction of long-range contacts
M Punta et al.
BIOINFORMATICS (2005)
A decade of CASP: progress, bottlenecks and prognosis in protein structure prediction
J Moult
CURRENT OPINION IN STRUCTURAL BIOLOGY (2005)
Framewise phoneme classification with bidirectional LSTM and other neural network architectures
A Graves et al.
NEURAL NETWORKS (2005)
Classifying 'drug-likeness' with kernel-based learning methods
KR Müller et al.
JOURNAL OF CHEMICAL INFORMATION AND MODELING (2005)
Energy landscapes and solved protein-folding problems
PG Wolynes
PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES (2005)
Development and large scale benchmark testing of the PROSPECTOR_3 threading algorithm
J Skolnick et al.
PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS (2004)
The ASTRAL Compendium in 2004
JM Chandonia et al.
NUCLEIC ACIDS RESEARCH (2004)
Random forest: A classification and regression tool for compound classification and QSAR modeling
V Svetnik et al.
JOURNAL OF CHEMICAL INFORMATION AND COMPUTER SCIENCES (2003)
Deep blue
M Campbell et al.
ARTIFICIAL INTELLIGENCE (2002)
Review: Protein secondary structure prediction continues to rise
B Rost
JOURNAL OF STRUCTURAL BIOLOGY (2001)
Progress in predicting inter-residue contacts of proteins with neural networks and correlated mutations
P Fariselli et al.
PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS (2001)
Generation and evaluation of dimension-reduced amino acid parameter representations by artificial neural networks
J Meiler et al.
JOURNAL OF MOLECULAR MODELING (2001)
Use of automatic relevance determination in QSAR studies using Bayesian neural networks
FR Burden et al.
JOURNAL OF CHEMICAL INFORMATION AND COMPUTER SCIENCES (2000)
分享论文
