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Graph Machine Learning (GML) is receiving growing interest within the pharmaceutical and biotechnology industries for its ability to model biomolecular structures, the functional relationships between them, and integrate multi-omic datasets - amongst other data types.
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The wnt-dependent signaling pathways as target in oncology drug discovery
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Structural biology in fragment-based drug design
Christopher W Murray and Tom L Blundell · 2010
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Network medicine: a network-based approach to human disease
Albert-László Barabási, Natali Gulbahce, and Joseph Loscalzo · 2011
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Weisfeiler-lehman graph kernels
Nino Shervashidze, Pascal Schweitzer, Erik Jan Van Leeuwen, Kurt Mehlhorn, and Karsten M Borgwardt · 2011
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A three-way model for collective learning on multi-relational data
Maximilian Nickel, Volker Tresp, and Hans-Peter Kriegel · 2011
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Graph regularized nonnegative matrix factorization for data representation
D. Cai, X. He, J. Han, and T. S. Huang · 2011
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Principles of early drug discovery
James P Hughes, Stephen Rees, S Barrett Kalindjian, and Karen L Philpott · 2011
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Target identification using drug affinity responsive target stability (darts)
Brett Lomenick, Gwanghyun Jung, James A Wohlschlegel, and Jing Huang · 2011
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How were new medicines discovered?
David C Swinney and Jason Anthony · 2011
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Recent advances in ligand-based drug design: relevance and utility of the conformationally sampled pharmacophore approach
Chayan Acharya, Andrew Coop, James E Polli, and Alexander D MacKerell · 2011
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Beyond natural antibodies: the power of in vitro display technologies
Andrew RM Bradbury, Sachdev Sidhu, Stefan Dübel, and John McCafferty · 2011
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Identification and validation of protein targets of bioactive small molecules
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Yeast two-hybrid methods and their applications in drug discovery
Amel Hamdi and Pierre Colas · 2012
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Targeting the tgf β \beta signalling pathway in disease
Rosemary J Akhurst and Akiko Hata · 2012
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Structural mass spectrometry in biologics discovery: advances and future trends
Jingjie Mo, Adrienne A Tymiak, and Guodong Chen · 2012
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Efficient estimation of word representations in vector space
Tomas Mikolov, Kai Chen, Greg Corrado, and Jeffrey Dean · 2013
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Translating embeddings for modeling multi-relational data
Antoine Bordes, Nicolas Usunier, Alberto Garcia-Duran, Jason Weston, and Oksana Yakhnenko · 2013
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Target identification and mechanism of action in chemical biology and drug discovery
Monica Schenone, Vlado Dančík, Bridget K Wagner, and Paul A Clemons · 2013
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Phenotypic screens as a renewed approach for drug discovery
Wei Zheng, Natasha Thorne, and John C McKew · 2013
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A large-scale evaluation of computational protein function prediction
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Deepwalk: Online learning of social representations
Bryan Perozzi, Rami Al-Rfou, and Steven Skiena · 2014
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Embedding entities and relations for learning and inference in knowledge bases
Bishan Yang, Wen-tau Yih, Xiaodong He, Jianfeng Gao, and Li Deng · 2014
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The discovery of first-in-class drugs: origins and evolution
Jörg Eder, Richard Sedrani, and Christian Wiesmann · 2014
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“new drug” designations for new therapeutic entities: new active substance, new chemical entity, new biological entity, new molecular entity
Sarah K Branch and Israel Agranat · 2014
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Quantum chemistry structures and properties of 134 kilo molecules
Raghunathan Ramakrishnan, Pavlo O Dral, Matthias Rupp, and O Anatole Von Lilienfeld · 2014
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Drugs derived from phage display: from candidate identification to clinical practice
Andrew E Nixon, Daniel J Sexton, and Robert C Ladner · 2014
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Social media and pharmacovigilance: a review of the opportunities and challenges
Richard Sloane, Orod Osanlou, David Lewis, Danushka Bollegala, Simon Maskell, and Munir Pirmohamed · 2015
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Utilizing social media data for pharmacovigilance: a review
Abeed Sarker, Rachel Ginn, Azadeh Nikfarjam, Karen O’Connor, Karen Smith, Swetha Jayaraman, Tejaswi Upadhaya, and Graciela Gonzalez · 2015
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Convolutional networks on graphs for learning molecular fingerprints
David K Duvenaud, Dougal Maclaurin, Jorge Iparraguirre, Rafael Bombarell, Timothy Hirzel, Alán Aspuru-Guzik, and Ryan P Adams · 2015
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A review of relational machine learning for knowledge graphs
Maximilian Nickel, Kevin Murphy, Volker Tresp, and Evgeniy Gabrilovich · 2015
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Limitations of algebraic approaches to graph isomorphism testing
Christoph Berkholz and Martin Grohe · 2015
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Heterogeneous network embedding via deep architectures
Shiyu Chang, Wei Han, Jiliang Tang, Guo-Jun Qi, Charu C Aggarwal, and Thomas S Huang · 2015
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Deep learning
Yann LeCun, Yoshua Bengio, and Geoffrey Hinton · 2015
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Zinc 15–ligand discovery for everyone
Teague Sterling and John J Irwin · 2015
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Choosing the right tool for the job: Rnai, talen, or crispr
Michael Boettcher and Michael T McManus · 2015
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Chopin: a web resource for the structural and functional proteome of mycobacterium tuberculosis
Bernardo Ochoa-Montaño, Nishita Mohan, and Tom L Blundell · 2015
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The support of human genetic evidence for approved drug indications
Matthew R Nelson, Hannah Tipney, Jeffery L Painter, Judong Shen, Paola Nicoletti, Yufeng Shen, Aris Floratos, Pak Chung Sham, Mulin Jun Li, Junwen Wang, et al · 2015
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Biologics and biosimilars
Palak K Patel, Caleb R King, and Steven R Feldman · 2015
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Comprehensive prediction of drug-protein interactions and side effects for the human proteome
Hongyi Zhou, Mu Gao, and Jeffrey Skolnick · 2015
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Line: Large-scale information network embedding
Jian Tang, Meng Qu, Mingzhe Wang, Ming Zhang, Jun Yan, and Qiaozhu Mei · 2015
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Innovation in the pharmaceutical industry: new estimates of r&d costs
Joseph A DiMasi, Henry G Grabowski, and Ronald W Hansen · 2016
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Single-cell analysis tools for drug discovery and development
James R Heath, Antoni Ribas, and Paul S Mischel · 2016
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Mass cytometry: single cells, many features
Matthew H Spitzer and Garry P Nolan · 2016
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Semi-supervised classification with graph convolutional networks
Thomas N Kipf and Max Welling · 2016
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node2vec: Scalable feature learning for networks
Aditya Grover and Jure Leskovec · 2016
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Complex embeddings for simple link prediction
Théo Trouillon, Johannes Welbl, Sebastian Riedel, Éric Gaussier, and Guillaume Bouchard · 2016
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Disgenet: a comprehensive platform integrating information on human disease-associated genes and variants
Janet Piñero, Àlex Bravo, Núria Queralt-Rosinach, Alba Gutiérrez-Sacristán, Jordi Deu-Pons, Emilio Centeno, Javier García-García, Ferran Sanz, and Laura I Furlong · 2016
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“omics”-informed drug and biomarker discovery: opportunities, challenges and future perspectives
Holly Matthews, James Hanison, and Niroshini Nirmalan · 2016
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Library-based display technologies: where do we stand?
Asier Galán, Lubos Comor, Anita Horvatić, Josipa Kuleš, Nicolas Guillemin, Vladimir Mrljak, and Mangesh Bhide · 2016
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Diffusion-convolutional neural networks
James Atwood and Don Towsley · 2016
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New tricks for old drugs
Nicola Nosengo · 2016
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In silico methods for drug repurposing and pharmacology
Rachel A Hodos, Brian A Kidd, Khader Shameer, Ben P Readhead, and Joel T Dudley · 2016
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A multiple kernel learning algorithm for drug-target interaction prediction
André CA Nascimento, Ricardo BC Prudêncio, and Ivan G Costa · 2016
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Clinical trial cycle times continue to increase despite industry efforts
Linda Martin, Melissa Hutchens, and Conrad Hawkins · 2017
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A genetics-led approach defines the drug target landscape of 30 immune-related traits
Hai Fang, Hans De Wolf, Bogdan Knezevic, Katie L Burnham, Julie Osgood, Anna Sanniti, Alicia Lledó Lara, Silva Kasela, Stephane De Cesco, Jörg K Wegner, et al · 2019
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Dynamic graph cnn for learning on point clouds
Yue Wang, Yongbin Sun, Ziwei Liu, Sanjay E Sarma, Michael M Bronstein, and Justin M Solomon · 2019
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Open targets platform: new developments and updates two years on
Denise Carvalho-Silva, Andrea Pierleoni, Miguel Pignatelli, ChuangKee Ong, Luca Fumis, Nikiforos Karamanis, Miguel Carmona, Adam Faulconbridge, Andrew Hercules, Elaine McAuley, et al · 2019
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Integrate multi-omics data with biological interaction networks using multi-view factorization autoencoder (mae)
Tianle Ma and Aidong Zhang · 2019
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Stabilizing variable selection and regression
Niklas Pfister, Evan G Williams, Jonas Peters, Ruedi Aebersold, and Peter Bühlmann · 2019
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The drug repurposing hub: a next-generation drug library and information resource
Steven M Corsello, Joshua A Bittker, Zihan Liu, Joshua Gould, Patrick McCarren, Jodi E Hirschman, Stephen E Johnston, Anita Vrcic, Bang Wong, Mariya Khan, Jacob Asiedu, Rajiv Narayan, Christopher C Mader, Aravind Subramanian, and Todd R Golub · 2017
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Protein interface prediction using graph convolutional networks
Alex Fout, Jonathon Byrd, Basir Shariat, and Asa Ben-Hur · 2017
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Neural message passing for quantum chemistry
Justin Gilmer, Samuel S Schoenholz, Patrick F Riley, Oriol Vinyals, and George E Dahl · 2017
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Representation learning on graphs: Methods and applications
William L Hamilton, Rex Ying, and Jure Leskovec · 2017
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Label informed attributed network embedding
Xiao Huang, Jundong Li, and Xia Hu · 2017
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Accelerated attributed network embedding
Xiao Huang, Jundong Li, and Xia Hu · 2017
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Molecular hypergraph grammar with its application to molecular optimization
Hiroshi Kajino · 2019
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Evaluating protein transfer learning with tape
Roshan Rao, Nicholas Bhattacharya, Neil Thomas, Yan Duan, Peter Chen, John Canny, Pieter Abbeel, and Yun Song · 2019
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Biological structure and function emerge from scaling unsupervised learning to 250 million protein sequences
Alexander Rives, Siddharth Goyal, Joshua Meier, Demi Guo, Myle Ott, C Lawrence Zitnick, Jerry Ma, and Rob Fergus · 2019
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Generative models for graph-based protein design
John Ingraham, Vikas Garg, Regina Barzilay, and Tommi Jaakkola · 2019
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Machine-learning-guided directed evolution for protein engineering
Kevin K Yang, Zachary Wu, and Frances H Arnold · 2019
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Attentive cross-modal paratope prediction
Andreea Deac, Petar VeliČković, and Pietro Sormanni · 2019
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Deep learning enables high-quality and high-throughput prediction of enzyme commission numbers
Jae Yong Ryu, Hyun Uk Kim, and Sang Yup Lee · 2019
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Intrinsically disordered proteins and structured proteins with intrinsically disordered regions have different functional roles in the cell
Antonio Deiana, Sergio Forcelloni, Alessandro Porrello, and Andrea Giansanti · 2019
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Intrinsically disordered proteins and their “mysterious”(meta) physics
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Donald J DiPette, Jamario Skeete, Emily Ridley, Norm RC Campbell, Patricio Lopez-Jaramillo, Sandeep P Kishore, Marc G Jaffe, Antonio Coca, Raymond R Townsend, and Pedro Ordunez · 2019
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