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。Accelerating De Novo Drug Design against Novel Proteins Using Deep Learning
Sowmya Ramaswamy Krishnan et al.
JOURNAL OF CHEMICAL INFORMATION AND MODELING (2021)
Transformer neural network for protein-specific de novo drug generation as a machine translation problem
Daria Grechishnikova
SCIENTIFIC REPORTS (2021)
De novo generation of hit-like molecules from gene expression signatures using artificial intelligence
Oscar Mendez-Lucio et al.
NATURE COMMUNICATIONS (2020)
PaccMann: a web service for interpretable anticancer compound sensitivity prediction
Joris Cadow et al.
NUCLEIC ACIDS RESEARCH (2020)
AITL: Adversarial Inductive Transfer Learning with input and output space adaptation for pharmacogenomics
Hossein Sharifi-Noghabi et al.
BIOINFORMATICS (2020)
Generative Model for Proposing Drug Candidates Satisfying Anticancer Properties Using a Conditional Variational Autoencoder
Sunghoon Joo et al.
ACS OMEGA (2020)
Predicting retrosynthetic pathways using transformer-based models and a hyper-graph exploration strategy
Philippe Schwaller et al.
CHEMICAL SCIENCE (2020)
Estimation of clinical trial success rates and related parameters
Chi Heem Wong et al.
BIOSTATISTICS (2019)
Next-generation characterization of the Cancer Cell Line Encyclopedia
Mahmoud Ghandi et al.
NATURE (2019)
From Target to Drug: Generative Modeling for the Multimodal Structure-Based Ligand Design
Miha Skalic et al.
MOLECULAR PHARMACEUTICS (2019)
Deep learning enables rapid identification of potent DDR1 kinase inhibitors
Alex Zhavoronkov et al.
NATURE BIOTECHNOLOGY (2019)
Off-target toxicity is a common mechanism of action of cancer drugs undergoing clinical trials
Ann Lin et al.
SCIENCE TRANSLATIONAL MEDICINE (2019)
AqSolDB, a curated reference set of aqueous solubility and 2D descriptors for a diverse set of compounds
Murat Cihan Sorkun et al.
SCIENTIFIC DATA (2019)
Toward Explainable Anticancer Compound Sensitivity Prediction via Multimodal Attention-Based Convolutional Encoders
Matteo Manica et al.
MOLECULAR PHARMACEUTICS (2019)
DrugBank 5.0: a major update to the DrugBank database for 2018
David S. Wishart et al.
NUCLEIC ACIDS RESEARCH (2018)
High-Throughput Gene Expression Profiles to Define Drug Similarity and Predict Compound Activity
Hans De Wolf et al.
ASSAY AND DRUG DEVELOPMENT TECHNOLOGIES (2018)
The rise of deep learning in drug discovery
Hongming Chen et al.
DRUG DISCOVERY TODAY (2018)
SCScore: Synthetic Complexity Learned from a Reaction Corpus
Connor W. Coley et al.
JOURNAL OF CHEMICAL INFORMATION AND MODELING (2018)
Automatic Chemical Design Using a Data-Driven Continuous Representation of Molecules
Rafael Gomez-Bombarelli et al.
ACS CENTRAL SCIENCE (2018)
Deep reinforcement learning for de novo drug design
Mariya Popova et al.
SCIENCE ADVANCES (2018)
FUn: a framework for interactive visualizations of large, high-dimensional datasets on the web
Daniel Probst et al.
BIOINFORMATICS (2018)
Plumbagin sensitizes breast cancer cells to tamoxifen-induced cell death through GRP78 inhibition and Bik upregulation
Anna Kawiak et al.
SCIENTIFIC REPORTS (2017)
Innovation in the pharmaceutical industry: New estimates of R&D costs
Joseph A. DiMasi et al.
JOURNAL OF HEALTH ECONOMICS (2016)
Surfactant-based drug delivery systems for treating drug-resistant lung cancer
Prabhjot Kaur et al.
DRUG DELIVERY (2016)
Tox21 Challenge to Build Predictive Models of Nuclear Receptor and Stress Response Pathways as Mediated by Exposure to Environmental Chemicals and Drugs
Ruili Huang et al.
FRONTIERS IN ENVIRONMENTAL SCIENCE (2016)
Cancer biomarker discovery is improved by accounting for variability in general levels of drug sensitivity in pre-clinical models
Paul Geeleher et al.
GENOME BIOLOGY (2016)
Using transcriptomics to guide lead optimization in drug discovery projects: Lessons learned from the QSTAR project
Bie Verbist et al.
DRUG DISCOVERY TODAY (2015)
Anticancer phytochemical analogs 37: Synthesis, characterization, molecular docking and cytotoxicity of novel plumbagin hydrazones against breast cancer cells
Prasad Dandawate et al.
BIOORGANIC & MEDICINAL CHEMISTRY LETTERS (2014)
Genomics and transcriptomics in drug discovery
Joaquin Dopazo
DRUG DISCOVERY TODAY (2014)
Embelin - a drug of antiquity: shifting the paradigm towards modern medicine
Radhika Poojari
EXPERT OPINION ON INVESTIGATIONAL DRUGS (2014)
The ChEMBL bioactivity database: an update
A. Patricia Bento et al.
NUCLEIC ACIDS RESEARCH (2014)
Estimation of the size of drug-like chemical space based on GDB-17 data
P. G. Polishchuk et al.
JOURNAL OF COMPUTER-AIDED MOLECULAR DESIGN (2013)
The Cancer Genome Atlas Pan-Cancer analysis project
John N. Weinstein et al.
NATURE GENETICS (2013)
Genomics of Drug Sensitivity in Cancer (GDSC): a resource for therapeutic biomarker discovery in cancer cells
Wanjuan Yang et al.
NUCLEIC ACIDS RESEARCH (2013)
Quantifying the chemical beauty of drugs
G. Richard Bickerton et al.
NATURE CHEMISTRY (2012)
Diagnosing the decline in pharmaceutical R&D efficiency
Jack W. Scannell et al.
NATURE REVIEWS DRUG DISCOVERY (2012)
Conjugates of plumbagin and phenyl-2-amino-1-thioglucoside inhibit MshB, a deacetylase involved in the biosynthesis of mycothiol
David W. Gammon et al.
BIOORGANIC & MEDICINAL CHEMISTRY (2010)
XIAP-mediated protection of H460 lung cancer cells against cisplatin
Yow-Jyun Cheng et al.
EUROPEAN JOURNAL OF PHARMACOLOGY (2010)
Extended-Connectivity Fingerprints
David Rogers et al.
JOURNAL OF CHEMICAL INFORMATION AND MODELING (2010)
OPINION Assessing the translatability of drug projects: what needs to be scored to predict success?
Martin Wehling
NATURE REVIEWS DRUG DISCOVERY (2009)
Protease-Activated Receptor-1 is Upregulated in Reactive Stroma of Primary Prostate Cancer and Bone Metastasis
Xiaotun Zhang et al.
PROSTATE (2009)
The NCI60 human tumour cell line anticancer drug screen
Robert H. Shoemaker
NATURE REVIEWS CANCER (2006)
ESOL: Estimating aqueous solubility directly from molecular structure
JS Delaney
JOURNAL OF CHEMICAL INFORMATION AND COMPUTER SCIENCES (2004)