Artificial intelligence in food and nutrition evidence: The challenges and opportunities based on a convening of content experts.
PNAS Nexus (2024). doi: 10.1093/pnasnexus/pgae461
Artificial intelligence in food and nutrition evidence: The challenges and opportunities based on a convening of content experts.
2024
Predicting clinical trial success for Clostridium difficile infections based on preclinical data.
Frontiers in Artificial Intelligence (2024). doi: 10.3389/frai.2024.1487335
Prediction of adolescent depression from prenatal and childhood data from ALSPAC using machine learning.
Scientific Reports (2024). doi: 10.1038/s41598-024-72158-9
FoodAtlas: Automated knowledge extraction of food and chemicals from literature.
Computers in Biology and Medicine (2024). doi: 10.1016/j.compbiomed.2024.109072
Combining proteomics and metabolomics to assess protein digestibility.
Abstract, NUTRITION 2024, American Society for Nutrition, Chicago, IL, 2024
Discovery of potent glycosidases enables quantification of smoke-derived phenolic glycosides through enzymatic hydrolysis.
Journal of Agricultural and Food Chemistry (2024). doi: 10.1021/acs.jafc.4c01247
Volatile organic compound-based predictive modeling of smoke taint in wine.
Journal of Agricultural and Food Chemistry (2024). doi: 10.1021/acs.jafc.3c07019
The AIFS Institute: Building a better food system through AI.
AI Magazine (2024). doi: 10.1002/aaai.12164
IL-23 induces CLEC5A+ IL-17A+ neutrophils and elicit skin inflammation associated with psoriatic arthritis.
Journal of Autoimmunity (2024). doi: 10.1016/j.jaut.2024.103167
2023
Profile characterization of biogenic amines in glioblastoma patients undergoing standard-of-care treatment.
Biomedicines (2023). doi: 10.3390/biomedicines11082261
Machine learning models to predict micronutrient profile in food after processing.
Current Research in Food Science (2023): 100500. doi: 10.1016/j.crfs.2023.100500
KGLM: Integrating knowledge graph structure in language models for link prediction.
Proceedings of the 12th Joint Conference on Lexical and Computational Semantics (*SEM 2023), Association for Computational Linguistics, Toronto, Canada, 2023. doi: 10.18653/v1/2023.starsem-1.20
Semi-automated construction of food composition knowledge base.
AI for Agriculture and Food Systems Workshop (AIAFS AAAI-23), The 37th AAAI Conference on Artificial Intelligence, Washington, D.C., 2023. doi: 10.48550/arXiv.2301.11322
2022
Audit lead selection and yield prediction from historical tax data using artificial neural networks.
PLOS One (2022). doi: 10.1371/journal.pone.0278121
Chardonnay marc as a new model for upcycled co-products in the food industry: concentration of diverse natural products chemistry for consumer health and sensory benefits.
Journal of Agricultural and Food Chemistry (2022). doi: 10.1021/acs.jafc.2c04519
Algorithmic lifestyle optimization.
Journal of the American Medical Informatics Association (2022). doi: 10.1093/jamia/ocac186
An early prediction model for canine chronic kidney disease based on routine clinical laboratory tests.
Scientific Reports (2022). doi: s41598-022-18793-6
A computational algorithm to assess the physiochemical determinants of T cell receptor dissociation kinetics.
Computational and Structural Biotechnology Journal (2022). doi: 10.1016/j.csbj.2022.06.048
Understanding the formation and mechanism of anticipatory responses in Escherichia coli.
International Journal of Molecular Sciences (2022). doi: 10.3390/ijms23115985
Knowledge integration and decision support for accelerated discovery of antibiotic resistance genes.
Nature Communications (2022). doi: 10.1038/s41467-022-29993-z
Special report: AI Institute for next generation food systems (AIFS).
Computers and Electronics in Agriculture (2022). doi: 10.1016/j.compag.2022.106819
2021
Reduced graphene oxide-metalloporphyrin sensors for human breath screening.
Applied Sciences (2021). doi: 10.3390/app112311290
Adaptive laboratory evolution for improved tolerance of isobutyl acetate in Escherichia coli.
Metabolic Engineering (2021). doi: 10.1016/j.ymben.2021.11.002
Integration of statistical inferences and machine learning algorithms for prediction of metritis cure in dairy cows.
Journal of Dairy Science (2021). doi: 10.3168/jds.2021-20262
Tolerance to glutaraldehyde in Escherichia coli mediated by overexpression of the aldehyde reductase YqhD by YqhC.
Frontiers in Microbiology (2021). doi: 10.3389/fmicb.2021.680553
Network‑based modeling of drug effects on disease module in systemic sclerosis.
Scientific Reports (2021). doi: 10.1038/s41598-020-70280-y
Biocide-induced emergence of antibiotic resistance in Escherichia coli.
Frontiers in Microbiology (2021). doi: 10.3389/fmicb.2021.640923
Methane and fatty acid metabolism pathways are predictive of Low-FODMAP diet efficacy for patients with irritable bowel syndrome.
Clinical Nutrition (2021). doi: 10.1016/j.clnu.2020.12.041
Preliminary techno-economic assessment of animal cell-based meat.
Foods (2021). doi: 10.1101/2020.09.10.292144
2020
Using word embeddings to learn a better food ontology.
Frontiers in Artificial Intelligence (2020). doi: 10.3389/frai.2020.584784
Discovery, design, and structural characterization of alkane producing enzymes across the ferritin-like superfamily.
Biochemistry (2020). doi: 10.1021/acs.biochem.0c00665
Novel classification of axial spondyloarthritis to predict radiographic progression using machine learning.
Clinical and Experimental Rheumatology (2020).
Accelerated knowledge discovery from omics data by optimal experimental design.
Nature Communications (2020). doi: 10.1038/s41467-020-18785-y
Short- and long-term transcriptomic responses of Escherichia coli to biocides: a systems analysis.
Applied and Environmental Microbiology (2020). doi: 10.1128/AEM.00708-20
The Computational Diet: A Review of Computational Methods Across Diet, Microbiome, and Health.
Frontiers in Microbiology (2020). doi:10.3389/fmicb.2020.00393
BWCNN: Blink to word, a real-time convolutional neural network approach
Proceesings of International Conference on Internet of Things (ICIOT 2020), Honolulu, 2020
2019
Predicting early risk of chronic kidney disease in cats using routine clinical laboratory tests and machine learning.
Journal of veterinary internal medicine (2019). doi:10.1111/jvim.15623
Nutrient Estimation from 24-Hour Food Recalls Using Machine Learning and Database Mapping: A Case Study with Lactose.
Nutrients (2019). doi:10.3390/nu11123045
Benzalkonium chlorides: Uses, regulatory status, and microbial resistance.
Applied and Environmental Microbiology (2019): AEM-00377. doi:10.1128/AEM.00377-19
Compendium of skin molecular signatures identifies key pathological features associated with fibrosis in systemic sclerosis.
Annals of the Rheumatic Diseases (2019): annrheumdis-2018. doi:10.1136/annrheumdis-2018-214778
Compendium of synovial signatures identifies pathologic characteristics for predicting treatment response in rheumatoid arthritis patients.
Clinical Immunology (2019). doi:10.1016/j.clim.2019.03.002
Population collapse and adaptive rescue during long‐term chemostat fermentation.
Biotechnology and bioengineering 116, no. 3 (2019): 693-703. doi:10.1002/bit.26898
2018
Application of machine learning in rheumatic disease research.
The Korean journal of internal medicine (2018). doi:10.3904/kjim.2018.349
Genetic Neural Networks: an artificial neural network architecture for capturing gene expression relationships.
Bioinformatics (2018). doi:10.1093/bioinformatics/bty945
Predicting the evolution of Escherichia coli by a data-driven approach.
Nature communications 9, no. 1 (2018): 3562. doi:10.1038/s41467-018-05807-z
Data integration and predictive modeling methods for multi-omics datasets.
Molecular omics 14, no. 1 (2018): 8-25. doi:10.1039/C7MO00051K
A network-based model for drug repurposing in Rheumatoid Arthritis.
BioRxiv (2018): 335679. doi:10.1101/335679
2017
DeepPep: Deep proteome inference from peptide profiles.
PLoS computational biology 13, no. 9 (2017): e1005661. doi:10.1371/journal.pcbi.1005661
Elucidating Substrate Promiscuity within the FabI Enzyme Family.
ACS chemical biology 12, no. 9 (2017): 2465-2473. doi:10.1021/acschembio.7b00400
Integrated omics analyses of retrograde signaling mutant delineate interrelated stress‐response strata.
The Plant Journal 91, no. 1 (2017): 70-84. doi:10.1111/tpj.13547
2016
The genetic and transcriptional basis of short and long term adaptation across multiple stresses in Escherichia coli.
Molecular biology and evolution 34, no. 3 (2016): 707-717. doi:10.1093/molbev/msw269
A parts database with consensus parameter estimation for synthetic circuit design.
ACS synthetic biology 5, no. 12 (2016): 1412-1420. doi:10.1021/acssynbio.5b00205
Multi-omics integration accurately predicts cellular state in unexplored conditions for Escherichia coli.
Nature communications 7 (2016): 13090. doi:10.1038/ncomms13090
A data‐driven, machine learning framework for optimal pest management in cotton.
Ecosphere 7, no. 3 (2016): e01263. doi:10.1002/ecs2.1263
Kinetic characterization of 100 glycoside hydrolase mutants enables the discovery of structural features correlated with kinetic constants.
PloS one11, no. 1 (2016): e0147596. doi:10.1371/journal.pone.0147596
2015
From data to optimal decision making: a data-driven, probabilistic machine learning approach to decision support for patients with sepsis.
JMIR medical informatics 3, no. 1 (2015): e11. doi:10.2196/medinform.3445
Microbial forensics: predicting phenotypic characteristics and environmental conditions from large-scale gene expression profiles.
PLoS computational biology 11, no. 3 (2015): e1004127. doi:10.1371/journal.pcbi.1004127 Erratum in: PLoS computational biology (2015): e1004617.
An Arabidopsis gene regulatory network for secondary cell wall synthesis.
Nature 517, no. 7536 (2015): 571. doi:10.1038/nature14099.
RiboTALE: A modular, inducible system for accurate gene expression control.
Scientific reports 5 (2015): 10658. doi:10.1038/srep10658.
Fast and accurate circuit design automation through hierarchical model switching.
ACS synthetic biology 4, no. 8 (2015): 890-897. doi:10.1021/sb500339k
A Distribution Adaptive Framework for Prediction Interval Estimation Using Nominal Variables.
arXiv preprint arXiv:1511.05688 (2015).
Parameter inference for gene circuit models
Proceedings of the 7th International Workshop on Bio-design Automation, IWBDA’15, Seattle, 2015
2014
Deciphering the genetic and transcriptional basis of cross-stress responses in Escherichia coli under complex evolutionary scenarios.
bioRxiv (2014): 010595. doi:10.1101/010595.
An integrative, multi‐scale, genome‐wide model reveals the phenotypic landscape of Escherichia coli.
Molecular systems biology 10, no. 7 (2014): 735. doi:10.15252/msb.20145108
Implications of an Enzymatic Biosensor for the Detection of Rancid Olive Oil.
Gold medal in International Genetically Engineered Machine (iGEM) (2014)
A systems biology analysis of brain microvascular endothelial cell lipotoxicity.
BMC systems biology 8, no. 1 (2014): 80. doi:10.1186/1752-0509-8-80
Optimal part and module selection for synthetic gene circuit design automation.
ACS synthetic biology 3, no. 8 (2014): 556-564. doi:10.1021/sb400139h
Integration of circuit design automation and genome-scale modeling
Proceedings of the 6th International Workshop on Bio-design Automation, IWBDA’14, Boston, 2014
An integrative genome-scale E. coli model and targeted experimentation methodology for systems and synthetic biology
2nd Conference on Quantitative Biology, q-bio’14, Hawaii, 2014
Petascale Simulations of Complex Biological Behavior in Fluctuating Environments
2nd NCSA Blue Waters Symposium for Petascale Science and Beyond, Champaign, IL, May, 2014
2013
Evolutionary potential, cross‐stress behavior and the genetic basis of acquired stress resistance in Escherichia coli.
Molecular systems biology 9, no. 1 (2013): 643. doi:10.1038/msb.2012.76
Microbial factories under control: auto-regulatory control through engineered stress-induced feedback.
Bioengineered 4, no. 1 (2013): 5-8. doi:10.4161/bioe.21935
Promoter element arising from the fusion of standard BioBrick parts.
ACS synthetic biology 2, no. 2 (2013): 111-120. doi:10.1021/sb300114d Erratum in: ACS synthetic biology (2013):351
SBROME: a scalable optimization and module matching framework for automated biosystems design.
ACS synthetic biology 2, no. 5 (2013): 263-273. doi:10.1021/sb300095m
From vital signs to clinical outcomes for patients with sepsis: a machine learning basis for a clinical decision support system.
Journal of the American Medical Informatics Association 21, no. 2 (2013): 315-325. doi:10.1136/amiajnl-2013-001815
A flood-based information flow analysis and network minimization method for gene regulatory networks.
BMC bioinformatics 14, no. 1 (2013): 137. doi:10.1186/1471-2105-14-137
Optimizing module matching for synthetic gene circuit design automation
Proceedings of the 5rd International Workshop on Bio-design Automation, IWBDA’13, London, 2013
Cross-stress protection in bacteria: an evolutionary perspective
Department of Microbiology and Environmental Toxicology, UCSC, 2013
Quorum Sensing in Bacteria
NSF BioMath Module, COMAP, pp. 1-42.
A automated synthetic gene circuit design tool based on mathematical optimization
1st Conference on Quantitative Biology, q-bio’13, Honolulu, Hawaii, 2013.
2012
Automatic design of synthetic gene circuits through mixed integer non-linear programming.
PloS one 7, no. 4 (2012): e35529. doi:10.1371/journal.pone.0035529
A synthetic biology approach to self-regulatory recombinant protein production in Escherichia coli.
Journal of biological engineering 6, no. 1 (2012): 2. doi:10.1186/1754-1611-6-2
Horizontal gene transfer dynamics and distribution of fitness effects during microbial in silico evolution.
BMC bioinformatics, vol. 13, no. 10, p. S13. BioMed Central, 2012. doi:10.1186/1471-2105-13-S10-S13
Guided evolution of in silico microbial populations in complex environments accelerates evolutionary rates through a step-wise adaptation.
BMC bioinformatics, vol. 13, no. 10, p. S10. BioMed Central, 2012. doi:10.1186/1471-2105-13-S10-S10
Transcriptional network analysis identifies BACH1 as a master regulator of breast cancer bone metastasis.
Journal of Biological Chemistry 287, no. 40 (2012): 33533-33544. doi:10.1074/jbc.M112.392332
Microbial evolution in vivo and in silico: methods and applications.
Integrative Biology 5, no. 2 (2012): 262-277. doi:10.1039/c2ib20095c
Scaling responsibly, Towards a reusable, modular, automated gene circuit design
Proceedings of the 3rd International Workshop on Bio-design Automation, IWBDA’12, San Francisco, 2012
A robust, library-based, optimization-driven method for automatic gene circuit design
2nd IEEE International Conference on Computational Advances in Bio and Medical Sciences (ICCABS), Las Vegas, NV, pp.1-6, 24-26, 2012
A Bayesian network for early diagnosis of sepsis patients: a basis for a clinical decision support system
2nd IEEE International Conference on Computational Advances in Bio and Medical Sciences (ICCABS), Las Vegas, NV, pp.1-5, 23-25, 2012
Guided step-wise adaptation of microbial populations
7th Annual Systems-to-Synthesis Symposium, San Diego, CA, 2012.
Network floods reveal regulatory control flows and minimal networks in synthetic and bacterial datasets
20th Annual Conference on Intelegent Systems for Molecular Biology, ISMB2012, Long Beach, CA. 2012.
Synthetic biology and evolutionary aspects of internal and external stress for industrial microbiology
4th ÖGMBT annual meeting, September 17-19, 2012, Graz, Austria.
Guided step-wise adaptation of microbial populations in silico and in vivo
7th Annual Systems-to-Synthesis Symposium, San Diego, CA, 2012
2011
Automated Design of Synthetic Gene Circuits through Linear Approximation and Mixed Integer Optimization
Proceedings of the 3rd International Workshop on Bio-design Automation, IWBDA2011, San Diego, 2011
In silico Evolution of Multi-scale Microbial Systems in the Presence of Mobile Genetic Elements and Horizontal Gene Transfer
ISBRA2011, Lecture Notes in Bioinformatics, LNBI 6674, pp.262-273, Springer, 2011
A Scalable Multi-scale Framework for Parallel Simulation and Visualization of Microbial Evolution
TeraGrid2011; Salt Lake City, Utah, 2011, DOI:10.1145/2016741.2016749 (Best Paper Award)
EVEVis: A Multi-Scale Visualization System for Dense Evolutionary Data
1st IEEE Symposium on Biological Data Visualization, pp. 143-150, Providence, Rhode Island, 2011
Facilitated Variation of in silico Microbial Populations Affects Evolutionary Rates
Poster and Talk, 7th International Symposium on Bioinformatics Research and Applications, Changsha, China, May 2011.
Automated Design of Synthetic Gene Circuits through Linear Approximation and Mixed Integer Optimization
Proceedings of the 3rd International Workshop on Bio-design Automation, IWBDA’11, San Diego, 2011.
Microbial Evolution in Stressful Environments: Theory and Experiments
Poster, 11th Conference on Microbial Genetics and Ecology, BAGECO’11, Corfu, Greece, 2011.
Self-regulatory circuits for recombinant protein production
Poster, 11th Conference on Microbial Genetics and Ecology, BAGECO’11, Corfu, Greece, 2011.
2010
Simulations of Microbial Evolution in Fluctuating Environments
Poster, 18th Annual International Conference on Intelligent Systems for Molecular Biology, ISMB’10, Boston, 2010.
Emergence of Robust Biological Networks in Petascale Simulations of Bacterial Evolution
Abstract, Extreme Scale I/O and Data Analysis Workshop, NSF/NCSA/TACC, Austin, TX, 2010
Large-scale Evolutionary Simulations of Complex Microbial Behaviors in Dynamic Environments
Poster, 9th Annual International Conference on Computational Systems Bioinformatics, CSB’10, Stanford, 2010.
2008
Predictive behavior within microbial genetic networks.
science 320, no. 5881 (2008): 1313-1317. doi:10.1126/science.1154456
2006
Symmetric and asymmetric multi-modality biclustering analysis for microarray data matrix.
Journal of bioinformatics and computational biology 4, no. 02 (2006): 275-298. doi:10.1142/S0219720006002065
2005
Multi-Metric and Multi-Substructure Biclustering Analysis for Gene Expression Data
CSB2005, Proceedings of the IEEE Computational Systems Bioinformatics Conference, pp.123-134, Stanford, California, 2005.
Multi-class Biclustering and Classification Based on Modeling of Gene Regulatory Networks
BIBE2005, Proceedings of the 5th IEEE Symposium on Bioengineering and Bioinformatics, pp. 89-96, Minneapolis, Minnesota, 2005
A Transcriptional Approach to Gene Clustering
CIBCB2005, Proceedings of the IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, pp.1-7, San Diego, California, 2005. (student paper award)
Gene Classification and Regulatory Prediction Based on Transcriptional Modeling.
Proceedings of the IEEE Symposium on Signal Processing and Information Technology, ISSPIT2005, pp. 29-34, Proceedings of the Firth IEEE International Symposium on Signal Processing and Information Technology, Athens, Greece, 2005.
2003
A Custom FPGA for the Simulation of Gene Regulatory Networks
GLSVLSI2003, Proceedings of the 13th ACM Great Lakes Symposium on VLSI, pp. 135-141, Washington D.C., 2003
2001
Comparison of DWT Scheduling Algorithms Alternatives on Programmable Platforms
ISCAS2001, Proceedings of the International Symposium on Circuits and Systems, , pp. 761-764, vol. 2, Sidney, Australia, 2001