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Transformer Query-Target Knowledge Discovery (TEND): Drug Discovery from CORD-19 [article]

Leo K. Tam and Xiaosong Wang and Daguang Xu
2020 arXiv   pre-print
Further, the query-target analysis is verified in a forward chaining analysis against the influenza drug clinical trials dataset, before adapted for COVID-19 drugs (combinations and side-effects) and on-going  ...  We present a RoBERTa transformer-based method that extends the masked language token prediction using query-target conditioning to treat the specificity challenge.  ...  Figure 1 :Figure 2 : 12 A RoBERTa-large transformer query-target method for drug discovery reveals positive and negative associations The black line represents influenza drugs receiving FDA approval.  ... 
arXiv:2012.04682v2 fatcat:bjfaifwzubgljfcndr2jluaqym

Machine Learning and Artificial Intelligence for the Prediction of Host–Pathogen Interactions: A Viral Case

Artur Yakimovich
2021 Infection and Drug Resistance  
Discovery of host-pathogen interactions (HPIs) conventionally involves a stepwise laborious research process.  ...  Yet, amid the global pandemic the urge for rapid discovery acceleration through the novel computational methodologies has become ever so poignant.  ...  method they named Transformer Query-Target Knowledge Discovery (TEND). 69 2] [73] Their data suggest that pretrained models may successfully be fine-tuned for HPI domain, gaining 4-7% performance over  ... 
doi:10.2147/idr.s292743 pmid:34456575 pmcid:PMC8385421 fatcat:ic5tgupdsna7jawljv7m3ppqoy

Drug Repurposing for COVID-19 via Knowledge Graph Completion [article]

Rui Zhang, Dimitar Hristovski, Dalton Schutte, Andrej Kastrin, Marcelo Fiszman, Halil Kilicoglu
2021 arXiv   pre-print
Methods: We propose a novel, integrative, and neural network-based literature-based discovery (LBD) approach to identify drug candidates from both PubMed and COVID-19-focused research literature.  ...  Objective: To discover candidate drugs to repurpose for COVID-19 using literature-derived knowledge and knowledge graph completion methods.  ...  Acknowledgments We thank François-Michel Lang, Leif Neve, and Jim Mork for their assistance with processing the CORD-19 dataset with SemRep and providing updates to SemMedDB.  ... 
arXiv:2010.09600v2 fatcat:un74tklxczhfzmndnau7q4ql3q

A Computational Inflection for Scientific Discovery [article]

Tom Hope, Doug Downey, Oren Etzioni, Daniel S. Weld, Eric Horvitz
2022 arXiv   pre-print
As society continues on its fast-paced digital transformation, so does humankind's collective scientific knowledge and discourse.  ...  We stand at the foot of a significant inflection in the trajectory of scientific discovery.  ...  Conversely, work in literature-based discovery [48] mines information from literature to generate new predictions (e.g., functions of materials [52] or drug targets [36] ) but is typically done in  ... 
arXiv:2205.02007v1 fatcat:d2dsit6msng6xhlpkb7ckgoi6q

Deep Learning applications for COVID-19

Connor Shorten, Taghi M. Khoshgoftaar, Borko Furht
2021 Journal of Big Data  
These limitations include Interpretability, Generalization Metrics, Learning from Limited Labeled Data, and Data Privacy.  ...  Within Life Sciences, our survey looks at how Deep Learning can be applied to Precision Diagnostics, Protein Structure Prediction, and Drug Repurposing.  ...  Drug repurposing candidates selected by querying knowledge graphs are very easily interpreted.  ... 
doi:10.1186/s40537-020-00392-9 pmid:33457181 pmcid:PMC7797891 fatcat:aokxo63z2rhdpfxo3egyf3xpcm

Subnetwork identification and chemical modulation for neural regeneration: A study combining network guided forest and heat diffusion model

Hui Wang, Gang Wang, Li-Da Zhu, Xuan Xu, Bo Diao, Hong-Yu Zhang
2018 Quantitative Biology  
The induction of neural regeneration is vital to the repair of spinal cord injury (SCI).  ...  This work also suggests an alternative approach for drug repositioning that can be easily extended to other disease phenotypes.  ...  Conventional drug-targeted mechanisms such as immune response and neurotrophic factors, are also well captured by subnetworks.  ... 
doi:10.1007/s40484-018-0159-0 fatcat:2vadvb6bf5ezroslkslngkkmzu

Applications of Artificial Intelligence in Healthcare

Shagufta Quazi, Rudra Prasad Saha, Manoj Kumar Singh
2022 Journal of Experimental Biology and Agricultural Sciences  
AI is launched in such a way that it has similar knowledge as a human but is more efficient.  ...  Discoveries and advancements will continue to push the AI frontier and expand the scope of its applications, with rapid developments expected in the future.  ...  The core aspect of "knowledge discovery from databases (KDD) is data mining, which includes the application of techniques that analyze the data, establish specific models and find previously unknown trends  ... 
doi:10.18006/2022.10(1).211.226 fatcat:43lctc3oa5gpfptrhcrnbvo5s4

A Glimpse of the First Eight Months of the COVID-19 Literature on Microsoft Academic Graph: Themes, Citation Contexts, and Uncertainties

Chaomei Chen
2020 Frontiers in Research Metrics and Analytics  
We demonstrate the application of the method in a study of the COVID-19 literature.  ...  As scientists worldwide search for answers to the overwhelmingly unknown behind the deadly pandemic, the literature concerning COVID-19 has been growing exponentially.  ...  recovery from the covid 19 pandemic Sars cov 2 an update on potential antivirals in light of sars cov antiviral drug discoveries Elshabrawy (2020) Frontiers in Research Metrics and Analytics | www.frontiersin.org  ... 
doi:10.3389/frma.2020.607286 pmid:33870064 pmcid:PMC8025977 fatcat:mhcaza5wp5gbrb3xkwgelixfrm

COVIDScholar: An automated COVID-19 research aggregation and analysis platform [article]

Amalie Trewartha, John Dagdelen, Haoyan Huo, Kevin Cruse, Zheren Wang, Tanjin He, Akshay Subramanian, Yuxing Fei, Benjamin Justus, Kristin Persson, Gerbrand Ceder
2020 arXiv   pre-print
COVIDScholar is a knowledge portal designed with the unique needs of the COVID-19 research community in mind, utilizing NLP to aid researchers in synthesizing the information spread across thousands of  ...  emergent research articles, patents, and clinical trials into actionable insights and new knowledge.  ...  All combined, these tools have allowed us to create much more targeted tools for literature search and knowledge discovery that would not be possible otherwise.  ... 
arXiv:2012.03891v1 fatcat:fcyluqglbvd35pswqlqevj3bim

Constructing Co-occurrence Network Embeddings to Assist Association Extraction for COVID-19 and Other Coronavirus Infectious Diseases

David Oniani, Guoqian Jiang, Hongfang Liu, Feichen Shen
2020 JAMIA Journal of the American Medical Informatics Association  
Objective As COVID-19 started its rapid emergence and gradually transformed into an unprecedented pandemic, the need for having a knowledge repository for the disease became crucial.  ...  To address this issue, a new COVID-19 machine readable dataset known as COVID-19 Open Research Dataset (CORD-19) has been released.  ...  Acknowledgement We thank the FHIRCat team for building the CORD-19-on-FHIR datasets and provide support on query template design. https://mc.manuscriptcentral.com/jamia Downloaded from https://academic.oup.com  ... 
doi:10.1093/jamia/ocaa117 pmid:32458963 pmcid:PMC7314034 fatcat:wvbklw5qlbgdhj57tnywzzvhly

The INCF Digital Atlasing Program: Report on Digital Atlasing Standards in the Rodent Brain

Michael Hawrylycz, Jyl Boline, Albert Burger, Tsutomu Hashikawa, G. Allan Johnson, Maryann Martone, Lydia Ng, Jonathan Nissanov, Luis Puelles, Seth Ruffins, Fons Verbeek, Ilya Zaslavsky
2009 Nature Precedings  
metadata from each source, to enable fast discovery queries.  ...  4, page 19 ).  ... 
doi:10.1038/npre.2009.4000 fatcat:zgzee4e5ivfo5gt6ouemrwfdsu

The INCF Digital Atlasing Program: Report on Digital Atlasing Standards in the Rodent Brain

Michael Hawrylycz, Jyl Boline, Albert Burger, Tsutomu Hashikawa, G. Allan Johnson, Maryann Martone, Lydia Ng, Jonathan Nissanov, Luis Puelles, Seth Ruffins, Fons Verbeek, Ilya Zaslavsky
2009 Nature Precedings  
metadata from each source, to enable fast discovery queries.  ...  4, page 19 ).  ... 
doi:10.1038/npre.2009.4000.1 fatcat:fezgneezbray5fwphzirvaw67a

Comparative transcriptome profiling of the human and mouse dorsal root ganglia

Pradipta Ray, Andrew Torck, Lilyana Quigley, Andi Wangzhou, Matthew Neiman, Chandranshu Rao, Tiffany Lam, Ji-Young Kim, Tae Hoon Kim, Michael Q. Zhang, Gregory Dussor, Theodore J. Price
2018 Pain  
Most of these show conserved enrichment in mDRG and were mined for known drug-gene product interactions.  ...  data from a variety of human and orthologous mouse tissues, including mouse DRG (mDRG).  ...  the perspective of DRG biology, and drug target discovery in the PNS.  ... 
doi:10.1097/j.pain.0000000000001217 pmid:29561359 pmcid:PMC6008200 fatcat:nui3m22wcbeh5kfdr3piihl6ru

Natural Products and Their Mimics as Targets of Opportunity for Discovery

Stephen F. Martin
2017 Journal of Organic Chemistry  
Diverse structural types of natural products and their mimics have served as targets of opportunity in our laboratory to inspire the discovery and development of new methods and strategies to assemble  ...  Furthermore, our efforts toward identifying novel compounds having useful biological properties led to the creation of new targets, many of which posed synthetic challenges that required the invention  ...  Indeed, all drugs interact with some biological target and thus mimic some, perhaps unknown, natural ligand.  ... 
doi:10.1021/acs.joc.7b01368 pmid:28738152 pmcid:PMC5653958 fatcat:ersv2tu56jdgdg3qu56nyfgrzi

Unlocking Big Data for better health

Steven Munevar
2017 Nature Biotechnology  
Validation (CTTV) and Roche drug discovery.  ...  We apply computer science methodologies to address drug and indication discovery, extracting knowledge from biomedical articles and drawing on ontologies and description logics to formalise biological  ... 
doi:10.1038/nbt.3918 pmid:28700551 fatcat:oqiurm5cgzec7lfenvjvlemxoy
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