Research graph
References from Drug target identification and validation using AI. Local targets link to admitted publications; unresolved targets remain external evidence.
The Role of AI in drug discovery
10.1002/cbic.202300816 · 2024 · External reference
Predicting the sequence specificities of DNA- and RNA-binding proteins by deep learning
10.1038/nbt.3300 · 2015 · External reference
Transcriptional regulatory networks underlying gene expression changes in Huntington’s disease
10.15252/msb.20167435 · 2018 · External reference
Multi‐Omics Factor Analysis—a framework for unsupervised integration of multi‐omics data sets
10.15252/msb.20178124 · 2018 · External reference
Deep learning in drug discovery: an integrative review and future challenges
10.1007/s10462-022-10306-1 · 2023 · External reference
Incorporating machine learning into established bioinformatics frameworks
10.3390/ijms22062903 · 2021 · External reference
High-throughput screening of natural product and synthetic molecule libraries for antibacterial drug discovery
10.3390/metabo13050625 · 2023 · External reference
Artificial intelligence in healthcare: transforming the practice of medicine
10.7861/fhj.2021-0095 · 2021 · External reference
Generalizing RNA velocity to transient cell states through dynamical modeling
10.1038/s41587-020-0591-3 · 2020 · External reference
Pattern classification with polynomial learning machines
2006 · External reference
Exploring the artificial intelligence and its impact in pharmaceutical sciences: insights toward the horizons where technology meets tradition
10.1111/cbdd.14639 · 2024 · External reference
QTL analysis of yield traits in an advanced backcross population derived from a cultivated Andean × wild common bean (Phaseolus vulgarisL.) cross
10.1007/s00122-006-0217-2 · 2006 · External reference
The role of AI in drug discovery: challenges, opportunities, and strategies
10.3390/ph16060891 · 2023 · External reference
Decision trees: from efficient prediction to responsible AI
10.3389/frai.2023.1124553 · 2023 · External reference
Extraction of relations between genes and diseases from text and large-scale data analysis: implications for translational research
10.1186/s12859-015-0472-9 · 2015 · External reference
Support vector machines for classification and regression
10.1039/b918972f · 2010 · External reference
Artificial intelligence enabled ChatGPT and large language models in drug target discovery, drug discovery, and development
10.1016/j.omtn.2023.08.009 · 2023 · External reference
The role of artificial neural networks on target validation in drug discovery and development
2016 · External reference
Omics data integration in cancer research: recent advances and future directions
2021 · External reference
Unresolved reference
2016 · External reference
A machine learning approach for genome-wide prediction of morbid and druggable human genes based on systems-level data
2010 · External reference
Effectively utilizing publicly available databases for cancer target evaluation
10.1093/narcan/zcad035 · 2023 · External reference
Machine learning in drug discovery: a review
10.1007/s10462-021-10058-4 · 2022 · External reference
Artificial intelligence in drug discovery: applications and techniques
10.1093/bib/bbab430 · 2022 · External reference
Artificial intelligence in the prediction of protein-ligand interactions: recent advances and future directions
10.1093/bib/bbab476 · 2022 · External reference
Machine learning-based prediction of rheumatoid arthritis with development of ACPA autoantibodies in the presence of non-HLA genes polymorphisms
10.1371/journal.pone.0300717 · 2024 · External reference
Dermatologist-level classification of skin cancer with deep neural networks
10.1038/nature21056 · 2017 · External reference
Advances in drug delivery systems, challenges and future directions
10.1016/j.heliyon.2023.e17488 · 2023 · External reference
Prioritizing target-disease associations with novel safety and efficacy scoring methods
10.1038/s41598-019-46293-7 · 2019 · External reference
The druggable genome and the importance of target class diversity
2017 · External reference
Artificial intelligence in omics
10.1016/j.gpb.2023.01.002 · 2022 · External reference
Population diversity and health disparities in drug target discovery
2022 · External reference
Revolutionizing medicinal chemistry: the application of artificial intelligence (AI) in early drug discovery
10.3390/ph16091259 · 2023 · External reference
Health natural language processing: methodology development and applications
10.2196/23898 · 2021 · External reference
Ethical considerations and concerns in the implementation of AI in pharmacy practice: a cross-sectional study
10.1186/s12910-024-01062-8 · 2024 · External reference
A high-throughput metabolomics method to predict high concentration cytotoxicity of drugs from low concentration profiles
10.1007/s11306-011-0386-0 · 2012 · External reference
The diversity of the human genome and its implications for personalized medicine
2018 · External reference
AI-driven drug discovery: accelerating the development of novel therapeutics in biopharmaceuticals
10.60087/jklst.vol3.n3.p.206-224 · 2024 · External reference
A landscape of pharmacogenomic interactions in cancer
10.1016/j.cell.2016.06.017 · 2016 · External reference
Artificial intelligence and bioinformatics: a journey from traditional techniques to smart approaches
2024 · External reference
A systematic approach to identify novel cancer drug targets using machine learning, inhibitor design and high-throughput screening
10.1186/s13073-014-0057-7 · 2014 · External reference
Recent advancements and challenges of NLP-based sentiment analysis: a state-of-the-art review
10.1016/j.nlp.2024.100059 · 2024 · External reference
Highly accurate protein structure prediction with AlphaFold
10.1038/s41586-021-03819-2 · 2021 · External reference
The cornucopia of meaningful leads: Applying deep adversarial autoencoders for new molecule development in oncology
10.18632/oncotarget.14073 · 2016 · External reference
Recent trends in artificial intelligence-driven identification and development of anti-neurodegenerative therapeutic agents
10.1007/s11030-021-10274-8 · 2021 · External reference
Meta-analysis of global and high throughput public gene array data for robust vascular gene expression discovery in chronic rhinosinusitis: implications in controlled release
10.1016/j.jconrel.2020.10.061 · 2021 · External reference
An analysis of disease-gene relationship from medline abstracts by DigSee
2017 · External reference
Artificial intelligence as a tool in drug discovery and development
10.5493/wjem.v14.i3.96042 · 2024 · External reference
Open Targets: a platform for therapeutic target identification and validation
10.1093/nar/gkw1055 · 2017 · External reference
Artificial intelligence in personalized medicine: applications and challenges
2022 · External reference
Addressing health disparities in drug discovery: a call for more diverse data
2018 · External reference
An in-depth review of AI-powered advancements in cancer drug discovery
10.1016/j.bbadis.2025.167680 · 2025 · External reference
Deep learning of the tissue-regulated splicing code
10.1093/bioinformatics/btu277 · 2014 · External reference
Medical image analysis using deep learning algorithms
2023 · External reference
Harnessing AI for the future of personalized drug discovery and therapy
2023 · External reference
Unraveling druggable cancer-driving proteins and targeted drugs using artificial intelligence and multi-omics analyses
10.1038/s41598-024-68565-7 · 2024 · External reference
Exploiting node content for multiview graph convolutional network and adversarial regularization
2020 · External reference
A Bayesian machine learning approach for drug target identification using diverse data types
10.1038/s41467-019-12928-6 · 2019 · External reference
Deep cell phenotyping and spatial analysis of multiplexed imaging with TRACERx-PHLEX
10.1038/s41467-024-48870-5 · 2024 · External reference
Machine learning on human muscle transcriptomic data for biomarker discovery and tissue-specific drug target identification
10.3389/fgene.2018.00242 · 2018 · External reference
AI-powered drug discovery platforms for target identification and validation: utilizing deep learning algorithms to enhance high-throughput screening and accelerate drug development processes
2021 · External reference
Artificial intelligence-driven drug development against autoimmune diseases
10.1016/j.tips.2023.04.005 · 2023 · External reference
GeneMANIA: a real-time multiple association network integration algorithm for predicting gene function
10.1186/gb-2008-9-s1-s4 · 2008 · External reference
GuiltyTargets: prioritization of novel therapeutic targets with network representation learning
10.1109/tcbb.2020.3003830 · 2022 · External reference
Artificial intelligence, big data and machine learning approaches in precision medicine & drug discovery
10.2174/18735592mtezsmdmnz · 2021 · External reference
Pharos: collating protein information to shed light on the druggable genome
10.1093/nar/gkw1072 · 2017 · External reference
AlphaFold, artificial intelligence (AI), and allostery
10.1021/acs.jpcb.2c04346 · 2022 · External reference
Chemical space for drug discovery: expanding the targetable proteome
2018 · External reference
GEMINI: integrative exploration of genetic variation and genome annotations
10.1371/journal.pcbi.1003153 · 2013 · External reference
MetaboAnalyst 6.0: towards a unified platform for metabolomics data processing, analysis and interpretation
10.1093/nar/gkae253 · 2024 · External reference
Artificial intelligence in drug discovery and development
10.1016/j.drudis.2020.10.010 · 2021 · External reference
Genomics is failing on diversity
10.1038/538161a · 2016 · External reference
A universal SNP and small-indel variant caller using deep neural networks
10.1038/nbt.4235 · 2018 · External reference
Deep reinforcement learning for de novo drug design
10.1126/sciadv.aap7885 · 2018 · External reference
Identification of therapeutic targets for amyotrophic lateral sclerosis using pandaomics—An AI-enabled biological target discovery platform
10.3389/fnagi.2022.914017 · 2022 · External reference
AI-powered therapeutic target discovery
10.1016/j.tips.2023.06.010 · 2023 · External reference
Introduction to artificial neural network (ANN) as a predictive tool for drug design, discovery, delivery, and disposition
2016 · External reference
Artificial intelligence and machine learning in precision and genomic medicine
10.1007/s12032-022-01711-1 · 2022 · External reference
Pharmacogenomics in diverse populations: opportunities and challenges
2015 · External reference
Role of artificial intelligence in revolutionizing drug discovery
2024 · External reference
AlphaFold accelerates artificial intelligence powered drug discovery: efficient discovery of a novel CDK20 small molecule inhibitor
10.1039/d2sc05709c · 2023 · External reference
Effectiveness of artificial intelligence for personalized medicine in neoplasms: a systematic review
10.1155/2022/7842566 · 2022 · External reference
Exploring the unkown druggable genome: AI’s potential
2023 · External reference
Natural language processing in medicine and ophthalmology: a review for the 21st-century clinician
10.1016/j.apjo.2024.100084 · 2024 · External reference
A knowledge graph to interpret clinical proteomics data
10.1038/s41587-021-01145-6 · 2022 · External reference
Target identification and mechanism of action in chemical biology and drug discovery
10.1038/nchembio.1199 · 2013 · External reference
10.1007/s11030-021-10326-z
10.1007/s11030-021-10326-z · External reference
Targeted therapy in cancer: the dynamic landscape of drug resistance
2016 · External reference
Exploring the artificial intelligence and machine learning models in the context of drug design difficulties and future potential for the pharmaceutical sectors
10.1016/j.ymeth.2023.09.010 · 2023 · External reference
DeepChem and its importance in Drug Discovery and Biology
2021 · External reference
From genome to clinic: the power of translational bioinformatics in improving human health
2024 · External reference
Unveiling the future of metabolic medicine: omics technologies driving personalized solutions for precision treatment of metabolic disorders
10.1016/j.bbrc.2023.09.064 · 2023 · External reference
Network medicine in the age of biomedical big data
10.3389/fgene.2019.00294 · 2019 · External reference
Why 90% of clinical drug development fails and how to improve it?
10.1016/j.apsb.2022.02.002 · 2022 · External reference
iNGNN-DTI:: prediction of drug–target interaction with interpretable nested graph neural network and pretrained molecule models
10.1093/bioinformatics/btae135 · 2024 · External reference
Impact of data pre-processing techniques on recurrent neural network performance in context of real-time drilling logs in an automated prediction framework
10.1016/j.petrol.2021.109760 · 2022 · External reference
AlphaFold-latest: revolutionizing protein structure prediction for comprehensive biomolecular insights and therapeutic advancements
10.1186/s43088-024-00503-y · 2024 · External reference
A new view of transcriptome complexity and regulation through the lens of local splicing variations
10.7554/elife.11752 · 2016 · External reference
Tools for target identification and validation
10.1016/j.cbpa.2004.06.001 · 2004 · External reference
Distributed high-performance computing methods for accelerating deep learning training
10.60087/jklst.v3.n3.p108-126 · 2024 · External reference
AI based drug screening process: from data mining to candidate drug validation
10.5376/bm.2024.15.0005 · 2024 · External reference
DeepGraphMine: end-to-end learning of molecule graphs
2020 · External reference
Targeting novel proteins for drug discovery: the untapped potential of the ‘unknome’
2019 · External reference
A systematic review of biologically-informed deep learning models for cancer: fundamental trends for encoding and interpreting oncology data
10.1186/s12859-023-05262-8 · 2023 · External reference
Recent advances in targeting the “undruggable” proteins: from drug discovery to clinical trials
10.1038/s41392-023-01589-z · 2023 · External reference
Revolutionizing drug discovery: the impact of artificial intelligence on advancements in pharmacology and the pharmaceutical industry
10.1016/j.ipha.2024.02.009 · 2024 · External reference
Unresolved reference
External reference
Phenotypic screening with deep learning identifies HDAC6 inhibitors as cardioprotective in a BAG3 mouse model of dilated cardiomyopathy
10.1126/scitranslmed.abl5654 · 2022 · External reference
Biomedical big data technologies, applications, and challenges for precision medicine: a review
10.1002/gch2.202300163 · 2024 · External reference
Industrializing AI/ML during the end-to-end drug discovery process
10.1016/j.sbi.2023.102528 · 2023 · External reference
DeepLigand: accurate prediction of MHC class I ligands using peptide embedding
10.1093/bioinformatics/btz330 · 2019 · External reference
Target identification among known drugs by deep learning from heterogeneous networks
10.1039/c9sc04336e · 2020 · External reference
Genome-wide identification of the genetic basis of amyotrophic lateral sclerosis
10.1016/j.neuron.2021.12.019 · 2022 · External reference
Deep biomarkers of aging and longevity: from research to applications
10.18632/aging.102475 · 2019 · External reference
OmicsNet: a web-based tool for creation and visual analysis of biological networks in 3D space
10.1093/nar/gky510 · 2018 · External reference
The impact of pricing schemes on cloud computing and distributed systems
10.60087/jklst.v3.n3.p206-224 · 2024 · External reference
Therapeutic target database update 2022: facilitating drug discovery with enriched comparative data of targeted agents
10.1093/nar/gkab953 · 2022 · External reference
Metascape provides a biologist-oriented resource for the analysis of systems-level datasets
10.1038/s41467-019-09234-6 · 2019 · External reference
The Role of AI in drug discovery
10.1002/cbic.202300816 · ExternalCitation · doi-reference
Biomedical big data technologies, applications, and challenges for precision medicine: a review
10.1002/gch2.202300163 · ExternalCitation · doi-reference
QTL analysis of yield traits in an advanced backcross population derived from a cultivated Andean × wild common bean (Phaseolus vulgarisL.) cross
10.1007/s00122-006-0217-2 · ExternalCitation · doi-reference
Machine learning in drug discovery: a review
10.1007/s10462-021-10058-4 · ExternalCitation · doi-reference
Deep learning in drug discovery: an integrative review and future challenges
10.1007/s10462-022-10306-1 · ExternalCitation · doi-reference
Recent trends in artificial intelligence-driven identification and development of anti-neurodegenerative therapeutic agents
10.1007/s11030-021-10274-8 · ExternalCitation · doi-reference
10.1007/s11030-021-10326-z
10.1007/s11030-021-10326-z · ExternalCitation · doi-reference
A high-throughput metabolomics method to predict high concentration cytotoxicity of drugs from low concentration profiles
10.1007/s11306-011-0386-0 · ExternalCitation · doi-reference
Artificial intelligence and machine learning in precision and genomic medicine
10.1007/s12032-022-01711-1 · ExternalCitation · doi-reference
Natural language processing in medicine and ophthalmology: a review for the 21st-century clinician
10.1016/j.apjo.2024.100084 · ExternalCitation · doi-reference
Why 90% of clinical drug development fails and how to improve it?
10.1016/j.apsb.2022.02.002 · ExternalCitation · doi-reference
An in-depth review of AI-powered advancements in cancer drug discovery
10.1016/j.bbadis.2025.167680 · ExternalCitation · doi-reference
Unveiling the future of metabolic medicine: omics technologies driving personalized solutions for precision treatment of metabolic disorders
10.1016/j.bbrc.2023.09.064 · ExternalCitation · doi-reference
Tools for target identification and validation
10.1016/j.cbpa.2004.06.001 · ExternalCitation · doi-reference
A landscape of pharmacogenomic interactions in cancer
10.1016/j.cell.2016.06.017 · ExternalCitation · doi-reference
Artificial intelligence in drug discovery and development
10.1016/j.drudis.2020.10.010 · ExternalCitation · doi-reference
Artificial intelligence in omics
10.1016/j.gpb.2023.01.002 · ExternalCitation · doi-reference
Advances in drug delivery systems, challenges and future directions
10.1016/j.heliyon.2023.e17488 · ExternalCitation · doi-reference
Revolutionizing drug discovery: the impact of artificial intelligence on advancements in pharmacology and the pharmaceutical industry
10.1016/j.ipha.2024.02.009 · ExternalCitation · doi-reference
Meta-analysis of global and high throughput public gene array data for robust vascular gene expression discovery in chronic rhinosinusitis: implications in controlled release
10.1016/j.jconrel.2020.10.061 · ExternalCitation · doi-reference
Genome-wide identification of the genetic basis of amyotrophic lateral sclerosis
10.1016/j.neuron.2021.12.019 · ExternalCitation · doi-reference
Recent advancements and challenges of NLP-based sentiment analysis: a state-of-the-art review
10.1016/j.nlp.2024.100059 · ExternalCitation · doi-reference
Artificial intelligence enabled ChatGPT and large language models in drug target discovery, drug discovery, and development
10.1016/j.omtn.2023.08.009 · ExternalCitation · doi-reference
Impact of data pre-processing techniques on recurrent neural network performance in context of real-time drilling logs in an automated prediction framework
10.1016/j.petrol.2021.109760 · ExternalCitation · doi-reference
Industrializing AI/ML during the end-to-end drug discovery process
10.1016/j.sbi.2023.102528 · ExternalCitation · doi-reference
Artificial intelligence-driven drug development against autoimmune diseases
10.1016/j.tips.2023.04.005 · ExternalCitation · doi-reference
AI-powered therapeutic target discovery
10.1016/j.tips.2023.06.010 · ExternalCitation · doi-reference
Exploring the artificial intelligence and machine learning models in the context of drug design difficulties and future potential for the pharmaceutical sectors
10.1016/j.ymeth.2023.09.010 · ExternalCitation · doi-reference
AlphaFold, artificial intelligence (AI), and allostery
10.1021/acs.jpcb.2c04346 · ExternalCitation · doi-reference
Genomics is failing on diversity
10.1038/538161a · ExternalCitation · doi-reference
Dermatologist-level classification of skin cancer with deep neural networks
10.1038/nature21056 · ExternalCitation · doi-reference
Predicting the sequence specificities of DNA- and RNA-binding proteins by deep learning
10.1038/nbt.3300 · ExternalCitation · doi-reference
A universal SNP and small-indel variant caller using deep neural networks
10.1038/nbt.4235 · ExternalCitation · doi-reference
Target identification and mechanism of action in chemical biology and drug discovery
10.1038/nchembio.1199 · ExternalCitation · doi-reference
Recent advances in targeting the “undruggable” proteins: from drug discovery to clinical trials
10.1038/s41392-023-01589-z · ExternalCitation · doi-reference
Metascape provides a biologist-oriented resource for the analysis of systems-level datasets
10.1038/s41467-019-09234-6 · ExternalCitation · doi-reference
A Bayesian machine learning approach for drug target identification using diverse data types
10.1038/s41467-019-12928-6 · ExternalCitation · doi-reference
Deep cell phenotyping and spatial analysis of multiplexed imaging with TRACERx-PHLEX
10.1038/s41467-024-48870-5 · ExternalCitation · doi-reference
Highly accurate protein structure prediction with AlphaFold
10.1038/s41586-021-03819-2 · ExternalCitation · doi-reference
Generalizing RNA velocity to transient cell states through dynamical modeling
10.1038/s41587-020-0591-3 · ExternalCitation · doi-reference
A knowledge graph to interpret clinical proteomics data
10.1038/s41587-021-01145-6 · ExternalCitation · doi-reference
Prioritizing target-disease associations with novel safety and efficacy scoring methods
10.1038/s41598-019-46293-7 · ExternalCitation · doi-reference
Unraveling druggable cancer-driving proteins and targeted drugs using artificial intelligence and multi-omics analyses
10.1038/s41598-024-68565-7 · ExternalCitation · doi-reference
Support vector machines for classification and regression
10.1039/b918972f · ExternalCitation · doi-reference
Target identification among known drugs by deep learning from heterogeneous networks
10.1039/c9sc04336e · ExternalCitation · doi-reference
AlphaFold accelerates artificial intelligence powered drug discovery: efficient discovery of a novel CDK20 small molecule inhibitor
10.1039/d2sc05709c · ExternalCitation · doi-reference
Artificial intelligence in drug discovery: applications and techniques
10.1093/bib/bbab430 · ExternalCitation · doi-reference
Artificial intelligence in the prediction of protein-ligand interactions: recent advances and future directions
10.1093/bib/bbab476 · ExternalCitation · doi-reference
iNGNN-DTI:: prediction of drug–target interaction with interpretable nested graph neural network and pretrained molecule models
10.1093/bioinformatics/btae135 · ExternalCitation · doi-reference
Deep learning of the tissue-regulated splicing code
10.1093/bioinformatics/btu277 · ExternalCitation · doi-reference
DeepLigand: accurate prediction of MHC class I ligands using peptide embedding
10.1093/bioinformatics/btz330 · ExternalCitation · doi-reference
Therapeutic target database update 2022: facilitating drug discovery with enriched comparative data of targeted agents
10.1093/nar/gkab953 · ExternalCitation · doi-reference
MetaboAnalyst 6.0: towards a unified platform for metabolomics data processing, analysis and interpretation
10.1093/nar/gkae253 · ExternalCitation · doi-reference
Open Targets: a platform for therapeutic target identification and validation
10.1093/nar/gkw1055 · ExternalCitation · doi-reference
Pharos: collating protein information to shed light on the druggable genome
10.1093/nar/gkw1072 · ExternalCitation · doi-reference
OmicsNet: a web-based tool for creation and visual analysis of biological networks in 3D space
10.1093/nar/gky510 · ExternalCitation · doi-reference
Effectively utilizing publicly available databases for cancer target evaluation
10.1093/narcan/zcad035 · ExternalCitation · doi-reference
GuiltyTargets: prioritization of novel therapeutic targets with network representation learning
10.1109/tcbb.2020.3003830 · ExternalCitation · doi-reference
Exploring the artificial intelligence and its impact in pharmaceutical sciences: insights toward the horizons where technology meets tradition
10.1111/cbdd.14639 · ExternalCitation · doi-reference
Deep reinforcement learning for de novo drug design
10.1126/sciadv.aap7885 · ExternalCitation · doi-reference
Phenotypic screening with deep learning identifies HDAC6 inhibitors as cardioprotective in a BAG3 mouse model of dilated cardiomyopathy
10.1126/scitranslmed.abl5654 · ExternalCitation · doi-reference
Effectiveness of artificial intelligence for personalized medicine in neoplasms: a systematic review
10.1155/2022/7842566 · ExternalCitation · doi-reference
GeneMANIA: a real-time multiple association network integration algorithm for predicting gene function
10.1186/gb-2008-9-s1-s4 · ExternalCitation · doi-reference
Extraction of relations between genes and diseases from text and large-scale data analysis: implications for translational research
10.1186/s12859-015-0472-9 · ExternalCitation · doi-reference
A systematic review of biologically-informed deep learning models for cancer: fundamental trends for encoding and interpreting oncology data
10.1186/s12859-023-05262-8 · ExternalCitation · doi-reference
Ethical considerations and concerns in the implementation of AI in pharmacy practice: a cross-sectional study
10.1186/s12910-024-01062-8 · ExternalCitation · doi-reference
A systematic approach to identify novel cancer drug targets using machine learning, inhibitor design and high-throughput screening
10.1186/s13073-014-0057-7 · ExternalCitation · doi-reference
AlphaFold-latest: revolutionizing protein structure prediction for comprehensive biomolecular insights and therapeutic advancements
10.1186/s43088-024-00503-y · ExternalCitation · doi-reference
GEMINI: integrative exploration of genetic variation and genome annotations
10.1371/journal.pcbi.1003153 · ExternalCitation · doi-reference
Machine learning-based prediction of rheumatoid arthritis with development of ACPA autoantibodies in the presence of non-HLA genes polymorphisms
10.1371/journal.pone.0300717 · ExternalCitation · doi-reference
Transcriptional regulatory networks underlying gene expression changes in Huntington’s disease
10.15252/msb.20167435 · ExternalCitation · doi-reference
Multi‐Omics Factor Analysis—a framework for unsupervised integration of multi‐omics data sets
10.15252/msb.20178124 · ExternalCitation · doi-reference
Deep biomarkers of aging and longevity: from research to applications
10.18632/aging.102475 · ExternalCitation · doi-reference
The cornucopia of meaningful leads: Applying deep adversarial autoencoders for new molecule development in oncology
10.18632/oncotarget.14073 · ExternalCitation · doi-reference
Artificial intelligence, big data and machine learning approaches in precision medicine & drug discovery
10.2174/18735592mtezsmdmnz · ExternalCitation · doi-reference
Health natural language processing: methodology development and applications
10.2196/23898 · ExternalCitation · doi-reference
Machine learning on human muscle transcriptomic data for biomarker discovery and tissue-specific drug target identification
10.3389/fgene.2018.00242 · ExternalCitation · doi-reference
Network medicine in the age of biomedical big data
10.3389/fgene.2019.00294 · ExternalCitation · doi-reference
Identification of therapeutic targets for amyotrophic lateral sclerosis using pandaomics—An AI-enabled biological target discovery platform
10.3389/fnagi.2022.914017 · ExternalCitation · doi-reference
Decision trees: from efficient prediction to responsible AI
10.3389/frai.2023.1124553 · ExternalCitation · doi-reference
Incorporating machine learning into established bioinformatics frameworks
10.3390/ijms22062903 · ExternalCitation · doi-reference
High-throughput screening of natural product and synthetic molecule libraries for antibacterial drug discovery
10.3390/metabo13050625 · ExternalCitation · doi-reference
The role of AI in drug discovery: challenges, opportunities, and strategies
10.3390/ph16060891 · ExternalCitation · doi-reference
Revolutionizing medicinal chemistry: the application of artificial intelligence (AI) in early drug discovery
10.3390/ph16091259 · ExternalCitation · doi-reference
AI based drug screening process: from data mining to candidate drug validation
10.5376/bm.2024.15.0005 · ExternalCitation · doi-reference
Artificial intelligence as a tool in drug discovery and development
10.5493/wjem.v14.i3.96042 · ExternalCitation · doi-reference
Distributed high-performance computing methods for accelerating deep learning training
10.60087/jklst.v3.n3.p108-126 · ExternalCitation · doi-reference
The impact of pricing schemes on cloud computing and distributed systems
10.60087/jklst.v3.n3.p206-224 · ExternalCitation · doi-reference
AI-driven drug discovery: accelerating the development of novel therapeutics in biopharmaceuticals
10.60087/jklst.vol3.n3.p.206-224 · ExternalCitation · doi-reference
A new view of transcriptome complexity and regulation through the lens of local splicing variations
10.7554/elife.11752 · ExternalCitation · doi-reference
Artificial intelligence in healthcare: transforming the practice of medicine
10.7861/fhj.2021-0095 · ExternalCitation · doi-reference
