Research

Funded by AHRQ, NIH, NSF, USDA, and industry, MUII core faculty and trainees actively conduct cutting-edge research in bioinformatics, health informatics, biomedical informatics, and geoinformatics. Trainees have opportunities to rotate to both dry and wet labs in computing, information science, plant & animal genomics, and clinical departments. Many of the plant genomics and phenomics research projects are in collaboration with the MU Interdisciplinary Plants Group (IPG), while healthcare related topics are coordinated with the School of Medicine, School of Nursing, School of Health Professions, and the Tiger Institute. MU is also in a unique position to tackle Big Data challenges in one health through fostering collaborations among Engineering, Vet Medicine, and Medicine to sponsor 18 doctoral students through the BD2K T32 training program.  To explore the specific types of extramural funding and the directors of projects, please visit the “Grants” list.

Labs

Bioinformatics, Data Mining and Machine Learning lab (BDM)

The research in BDM lab is focused on developing machine learning and data mining methods to analyze big biomedical data for solving fundamental problems in biomedical sciences. Currently, we are developing bioinformatics algorithms and tools for protein structure and function prediction, 3D genomics, biological network modeling, and omics data analysis. The research is funded by both National Institutes of Health (NIH_ and National Science Foundation (NSF).

Data Science Lab

 Our lab develops powerful statistical and computational methods for the analysis of large and complex datasets, longitudinal data, survival data, and applied them to public health, medicine and social sciences, among others. In addition, we collaborate and consult with epidemiologists and clinicians on study design, data analysis and results interpretation.

Dermatology Department Lab

The faculty and staff at the University of Missouri's Department of Dermatology are dedicated to providing high quality dermatological care for our patients, exceptional educational experiences for our residents and students, and the ongoing pursuit of new knowledge and scholarship. We provide dermatology care for patients at University of Missouri Health Care Hospital and Clinics, the Harry S. Truman Memorial Veterans' Hospital, and the Ellis Fischel Cancer Center. We also have been conducting teledermatology clinics in rural, underserved areas of Missouri for over 15 years.

Digital Biology Laboratory

The research focus of Digital Biology Laboratory (DBL) is Bioinformatics and Computational Biology. The lab works on development of novel computational methods, algorithms, software and information systems, as well as on broad applications of these tools and other informatics resources for various biological and medical problems. Research topics include application of deep learning in biological and medical data analysis and prediction, protein structure prediction, high-throughput biological data analysis, protein post-translation modification analysis, and computational biology studies of plants, cancers, and microbes. The lab has collaborated with dozens of research labs. 

 

Interdisciplinary Data Analytics and Search (iDAS) Lab

The iDAS Lab hosts trainees and researchers in computational science and informatics to design algorithms and develop methods for faster and more accurate predicative analytics and information search through large-scale information sources in biomedicine, engineering, and plant sciences with storytelling values for actionable decisions. Building upon rich research foundations, the lab has four active research directions in exploratory mining, Big Data search, visual knowledge retrievals, and block chains.  All theoretical works developed in the iDAS lab are required to be tested on real-world data sets, such as HealthFacts® (60 million patients), National Impatient Sample (NIS), TCGA data, PDB, Simons Foundation Autism Research Initiative data, etc.

Pires Lab

Research in our lab broadly encompasses plant evolutionary biology- from phylogenetic studies in plant diversity to genome-wide analyses of gene expression. Current investigations are directed at molecular systematics and comparative genomics, with a particular focus on the evolution and ecology of polyploid plants. 

RNA Computational Biology Lab

Dr. Chen's lab has been developing computational methods for RNA structure and function and applications of the computational models to therapeutic designs. A main research method used in the lab is to design and implement knowledge-based database and to extract structure and function information from the database.  Examples of the current research efforts include RNA 3D structure prediction based on rules derived from the known structure database, prediction of metal ion binding sites on nucleic acids through data training, sgRNA design and genome-wide off-target prediction for CRISPR-Cas9 gene editing system, and RNA-based drug design.

The Decker Computational Genomics Group

The Decker Computational Genomics Group applies evolutionary biology to domesticated cattle, and other species as collaborations arise. We use the history of cattle populations to create genomic selection tools to improve cattle. Working at the intersection of two disciplines (bovine genomics and evolutionary biology) allows us to access large datasets, often produced for other research or commercial purposes. Our research program also has a transnational component in which we take basic research and transform it into decision support tools for farmers and ranchers.

The King Lab

In the King Lab, we are trying to understand the genetic basis and evolution of organismal allocation patterns. The core life processes for every organism, such as surviving in the environment, finding food and mates, and reproducing, require the organism to allocate some of its limited resources to these functions. Different selective pressures have produced the diversity of strategies that we see within and among species in how and when to allocate resources to different structures and functions. We use both computational and empirical techniques to try to understand both how different allocation strategies evolve and the underlying genetic architecture of this highly complex trait.

The Meyers Lab

Dr. Meyers's current research includes programs that emphasize bioinformatics and plant functional genomics. These programs include (1) analyses of small RNA, DNA methylation and the genomes of rice, Arabidopsis and other species using short-read DNA sequencing technologies, (2) development and implementation of novel informatics approaches for the storage, analysis, display, and public release of these data, (3) functional and evolutionary analyses of several gene families of interest, particularly miRNAs, phasiRNAs and the proteins involved in their biogenesis, as well as NB-LRR disease resistance genes.

Translational & Cancer Bioinformatics Laboratory

The TCBI lab conducts research in translational and cancer bioinformatics, imaging informatics, pathology informatics, computational epigenetics, and precision medicine informatics under the leadership of Dr. Dmitriy Shin. We draw from the experience of leading pathologists to study computational reasoning over molecular knowledge networks, function of long non-coding RNAs, molecular underpinnings of intra-tumor heterogeneity, brain damage imaging, diagnostics heuristics, pathway analysis, knowledge representation and knowledge complexity reduction, and many other topics. The lab is part of Pathology Informatics, a division of Pathology and Anatomical Sciences Department, and MU Informatics Institute.

Virtualization, Multimedia and Networking Lab (VIMAN)

At VIMAN Lab, we investigate novel methods to model, measure, manage and secure distributed computing applications that have real-time resource allocation needs and require high-speed networks. With broadband access and cloud computing becoming integral in our society, end-user applications (e.g., video-on-demand, videoconferencing, remote visualization, remote instrumentation, real-time data analytics) are increasingly becoming data-intensive, mobility-supported and network-dependent. Consequently, we are motivated by the challenges in studying theoretical foundations as well as developing tools for networks and cloud platforms. We strive for meeting the end-user Quality of Experience (QoE) expectations in applications (e.g., healthcare, advanced manufacturing, public safety, new media, bioinformatics).

Vision-Guided and Intelligent Robotics Lab (ViGIR)

In the ViGIR lab, we conduct research in areas such as: Computer Vision, Pattern Recognition and Robotics. We develop models to represent the world as perceived by cameras and other sensors and we devise algorithms that make use of such models to extract real time information from a sensory network in order to guide robots to perform various tasks. Our main goal is to build new Human-Robot Interfaces that can be used in robotic assistive technology, augmented reality, automation, tele-operation, etc....

Zou Lab

We are developing computational methods to calculate binding free energies for ligand-receptor complexes. The derived energy models are applied to protein-substrate interactions, protein-protein interactions, and structure-based drug design. We are also developing new docking algorithms to account for protein flexibility. Methods used in our laboratory include computer modeling, simulation and graphics display. Additional application includes modeling of structure-function relationship of membrane proteins.

Chemical Ecology Lab

The Schultz-Appel Chemical Ecology Lab at the University of Missouri is directed by Jack Schultz and Heidi Appel of the Plant Sciences Division, College of Agriculture, Food and Natural Resources. Our lab addresses broad ecological and evolutionary questions in insect and plant science by using chemical, biochemical, and molecular methods.

MU Soybean Genomics Laboratory

The laboratory is directed by Dr. Henry T. Nguyen, Missouri Soybean Merchandising Council (MSMC) Endowed Professor of Genetics and Soybean Biotechnology. Research interests in the laboratory focus on the molecular genetics of plant stress tolerance and the application of genomics and genetic engineering technologies to soybean improvement.ethods.

National Center for Soybean Biotechnology

By conducting and providing research in soybean genomics and biotechnology, we contribute to the genetic improvement of soybeans for food, human health, and industrial uses, while increasing the profitability of the U.S. soybean industry.

Plant Root Genomics Consortium

Plant roots play a vital role in water and mineral acquisition, and are essential for plant growth and development. Under conditions of drought, roots can adapt to continue growth while at the same time producing and sending early warning signals to shoots which inhibit plant growth above ground. The plant root system, often referred to as "the hidden half," has received much less attention compared to the shoot. We have formed a Plant Root Genomics Consortium dedicated to root genetics and physiology. The aim of this consortium is to develop an understanding of the molecular mechanisms used by plant roots to acquire water and minerals from the soil, to elucidate the role roots play in adaptation to drought conditions, and to transfer this knowledge to crop improvement through biotechnology.

Tang Lab

Situated in the new Schweitzer Hall Addition, Department of Biochemistry at the University of Missouri - Columbia, the Tang laboratory utilizes state-of-the-art nuclear magnetic resonance or NMR and various biochemical/biophysical/computational techniques to characterize macromolecular structure and dynamics in solution.

Grants

The MUII core faculty received substantial competitive funding from the National Science Foundation (NSF), the National Institutes of Health (NIH), the National Institute of Justice (NIJ), US Army, Missouri Soybean Merchandising Council and Industries.

FacultySponserProject TitleAmountDuration
Dr. Gregory Alexander (PI)AHRQA National Report of Quality Measures and Information Technology in Nursing Homes-Renewal$1,995,52209/30/2017-
10/29/2022
Elizabeth King (PI)NSFQuantitative genetics of learning and memory in Drosophila$462,90006/15/2017-
05/31/2020
Shi-Jie Chen (PI)NIHNew computational tools for predicting ion effects in RNA structures$1,219,72102/01/2017-
01/31/2021
Prasad Calyam (Co-PI)NSFUS Ignite: A Networked Virtual Reality Platform for Online Social Learning of Youth with Autism Spectrum Disorders$599,16002/01/2017-
01/31/2020
Prasad Calyam (PI)NSFREU SITE: Research in Consumer Networking Technologies$359,99902/01/2017-
01/31/2020
Prasad Calyam (PI)NSFUS Ignite: Resilient Virtual Path Management for Scalable Data-intnesive Computing at Networ-Edges$203,81501/01/2017-
12/31/2019
Jeffery Belden (Co-I)NIHOptimizing Display of Blood Pressure Data to Support Clinical Decision Making$2,272,27201/04/2015-
03/31/2020
Blake Meyers (PI)NSFIOS: The Function and Evolution of Plant Phased siRNAs in Singling Pathways and Microbial Interactions$422,71501/01/2016-
08/31/2017
Jared Decker (PI)USDANational Animal Genome Research Program$50,00001/01/2013-
09/30/2018
Jared Decker (PI)USDAValidation of a Multi-Breed Beef Tenderness Genomic Prediction Test using Retail Steaks$15,00001/01/2013-
09/30/2018
Gregory Alexander (PI)AHRQA National Report of Nursing Home Quality Measures and Information Technology$999,95201/11/2013-
10/31/2017
Chi-Ren Shyu (PI)NSFREU Site: Educating for the Grand Challenges at the Intersection of Biocomplexity and High-performance Computing$316,37801/04/2017-
07/31/2017
J. Pires (PI)NSFPoloploidy and Plasticity in the Crop Brassicas$2,179,71601/08/2017-
07/31/2017
Chi-Ren Shyu (PI)NSFMRI: Acquisition of Instrument of Data-intensive Application with Hybrid Cloud Computing Needs$600,48009/01/2014-
08/31/2017
Xiaoqin Zou (PI)NIHDatabase and Software Development for Protein-Nucleic Acid Structure Prediction$1,461,94001/02/2015-
11/30/2017
Jianlin Cheng (PI)NIHIntegrated Prediction and Validation of Protein Structures$1,300,00001/08/2016-
08/31/2019
Chi-Ren Shyu (PI)NIHT32: Massive and Complex Data Analysis Pre-Doctoral Training in One Health$1,453,55501/04/2016-
03/31/2021

Publications

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2017

Reyes-Chin-Wo, S; Wang, Z; Yang, X; Kozik, A; Arikit, S; Song, C; Xia, L; Froenicke, L; Lavelle, D O; Truco, M J; Xia, R; Zhu, S; Xu, C; Xu, H; Xu, X; Cox, K; Korf, I; Meyers, B C; Michelmore, R W

Genome assembly with in vitro proximity ligation data and whole-genome triplication in lettuce (Journal Article)

Nat Commun, 8 , pp. 14953, 2017, ISSN: 2041-1723 (Electronic) 2041-1723 (Linking).

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Jamil, K M; Hydes, T J; Cheent, K S; Cassidy, S A; Traherne, J A; Jayaraman, J; Trowsdale, J; Alexander, G J; Little, A M; McFarlane, H; Heneghan, M A; Purbhoo, M A; Khakoo, S I

STAT4-associated natural killer cell tolerance following liver transplantation (Journal Article)

Gut, 66 (2), pp. 352-361, 2017, ISSN: 1468-3288 (Electronic) 0017-5749 (Linking).

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Rutkow, L; Vernick, J S; Alexander, G C

More States Should Regulate Pain Management Clinics to Promote Public Health (Journal Article)

Am J Public Health, 107 (2), pp. 240-243, 2017, ISSN: 1541-0048 (Electronic) 0090-0036 (Linking).

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Ji, S G; Juran, B D; Mucha, S; Folseraas, T; Jostins, L; Melum, E; Kumasaka, N; Atkinson, E J; Schlicht, E M; Liu, J Z; Shah, T; Gutierrez-Achury, J; Boberg, K M; Bergquist, A; Vermeire, S; Eksteen, B; Durie, P R; Farkkila, M; Muller, T; Schramm, C; Sterneck, M; Weismuller, T J; Gotthardt, D N; Ellinghaus, D; Braun, F; Teufel, A; Laudes, M; Lieb, W; Jacobs, G; Beuers, U; Weersma, R K; Wijmenga, C; Marschall, H U; Milkiewicz, P; Pares, A; Kontula, K; Chazouilleres, O; Invernizzi, P; Goode, E; Spiess, K; Moore, C; Sambrook, J; Ouwehand, W H; Roberts, D J; Danesh, J; Floreani, A; Gulamhusein, A F; Eaton, J E; Schreiber, S; Coltescu, C; Bowlus, C L; Luketic, V A; Odin, J A; Chopra, K B; Kowdley, K V; Chalasani, N; Manns, M P; Srivastava, B; Mells, G; Sandford, R N; Alexander, G; Gaffney, D J; Chapman, R W; Hirschfield, G M; de Andrade, M; Consortium, Uk-Psc ; International, Genetics Consortium I B D; International, Study Group P S C; Rushbrook, S M; Franke, A; Karlsen, T H; Lazaridis, K N; Anderson, C A

Genome-wide association study of primary sclerosing cholangitis identifies new risk loci and quantifies the genetic relationship with inflammatory bowel disease (Journal Article)

Nat Genet, 49 (2), pp. 269-273, 2017, ISSN: 1546-1718 (Electronic) 1061-4036 (Linking).

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Johnson, K L; Cassin, A M; Lonsdale, A; Wong, G K; Soltis, D; Miles, N W; Melkonian, M; Melkonian, B; Deyholos, M K; Leebens-Mack, J; Rothfels, C J; Stevenson, D W; Graham, S W; Wang, X; Wu, S; Pires, J C; Edger, P P; Carpenter, E J; Bacic, A; Doblin, M S; Schultz, C J

Insights into the evolution of hydroxyproline rich glycoproteins from 1000 plant transcriptomes (Journal Article)

Plant Physiol, 2017, ISSN: 1532-2548 (Electronic) 0032-0889 (Linking).

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Joshi, T; Wang, J; Zhang, H; Chen, S; Zeng, S; Xu, B; Xu, D

The Evolution of Soybean Knowledge Base (SoyKB) (Journal Article)

Methods Mol Biol, 1533 , pp. 149-159, 2017, ISSN: 1940-6029 (Electronic) 1064-3745 (Linking).

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Juan Cai, W; Yin, L; Kang, Q; Chen Zeng, Z; Liang Wang, S; Cheng, J

The Serum Pepsinogen Test as a Predictor of Kazakh Gastric Cancer (Journal Article)

Sci Rep, 7 , pp. 43536, 2017, ISSN: 2045-2322 (Electronic) 2045-2322 (Linking).

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Shafiekhani, A; Kadam, S; Fritschi, F B; DeSouza, G N

Vinobot and Vinoculer: Two Robotic Platforms for High-Throughput Field Phenotyping (Journal Article)

Sensors (Basel), 17 (1), 2017, ISSN: 1424-8220 (Electronic) 1424-8220 (Linking).

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Sheets, L; Petroski, G F; Zhuang, Y; Phinney, M A; Ge, B; Parker, J C; Shyu, C R

Combining Contrast Mining with Logistic Regression To Predict Healthcare Utilization in a Managed Care Population (Journal Article)

Appl Clin Inform, 8 (2), pp. 430-446, 2017, ISSN: 1869-0327 (Electronic).

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Char, S N; Neelakandan, A K; Nahampun, H; Frame, B; Main, M; Spalding, M H; Becraft, P W; Meyers, B C; Walbot, V; Wang, K; Yang, B

An Agrobacterium-delivered CRISPR/Cas9 system for high-frequency targeted mutagenesis in maize (Journal Article)

Plant Biotechnol J, 15 (2), pp. 257-268, 2017, ISSN: 1467-7652 (Electronic) 1467-7644 (Linking).

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Kolicheski, A; Barnes Heller, H L; Arnold, S; Schnabel, R D; Taylor, J F; Knox, C A; Mhlanga-Mutangadura, T; O'Brien, D P; Johnson, G S; Dreyfus, J; Katz, M L

Homozygous PPT1 Splice Donor Mutation in a Cane Corso Dog With Neuronal Ceroid Lipofuscinosis (Journal Article)

J Vet Intern Med, 31 (1), pp. 149-157, 2017, ISSN: 1939-1676 (Electronic) 0891-6640 (Linking).

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Kolicheski, A L; Johnson, G S; Mhlanga-Mutangadura, T; Taylor, J F; Schnabel, R D; Kinoshita, T; Murakami, Y; O'Brien, D P

A homozygous PIGN missense mutation in Soft-Coated Wheaten Terriers with a canine paroxysmal dyskinesia (Journal Article)

Neurogenetics, 18 (1), pp. 39-47, 2017, ISSN: 1364-6753 (Electronic) 1364-6745 (Linking).

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Cheng, C; Zandi, P; Stuart, E; Lin, C H; Su, P Y; Alexander, G C; Lan, T H

Association Between Lithium Use and Risk of Alzheimer's Disease (Journal Article)

J Clin Psychiatry, 78 (2), pp. e139-e145, 2017, ISSN: 1555-2101 (Electronic) 0160-6689 (Linking).

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Kumar, S R; Bryan, J N; Esebua, M; Amos-Landgraf, J; May, T J

Testis specific Y-like 5: gene expression, methylation and implications for drug sensitivity in prostate carcinoma (Journal Article)

BMC Cancer, 17 (1), pp. 158, 2017, ISSN: 1471-2407 (Electronic) 1471-2407 (Linking).

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Kumar, S R; Kim, D Y; Henry, C J; Bryan, J N; Robinson, K L; Eaton, A M

Programmed death ligand 1 is expressed in canine B cell lymphoma and downregulated by MEK inhibitors (Journal Article)

Vet Comp Oncol, 2017, ISSN: 1476-5829 (Electronic) 1476-5810 (Linking).

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Clarke, M A; Moore, J L; Steege, L M; Koopman, R J; Belden, J L; Canfield, S M; Kim, M S

Toward a patient-centered ambulatory after-visit summary: Identifying primary care patients' information needs (Journal Article)

Inform Health Soc Care, pp. 1-16, 2017, ISSN: 1753-8165 (Electronic) 1753-8157 (Linking).

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Tan, J; Bae, S; Segal, J B; Zhu, J; Segev, D L; Alexander, G C; McAdams-DeMarco, M

Treatment of atrial fibrillation with warfarin among older adults with end stage renal disease (Journal Article)

J Nephrol, 2017, ISSN: 1724-6059 (Electronic) 1121-8428 (Linking).

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Cohen, R; Sarceno Cardona, J; Solares Navarro, E; Padilla, N; Reyes, L; Javier Pinto Villar, R; Masuoka, P; Bernart, C; Peruski, L F; Bryan, J P

Outbreak Investigation of Plasmodium vivax Malaria in a Region of Guatemala Targeted for Malaria Elimination (Journal Article)

Am J Trop Med Hyg, 2017, ISSN: 1476-1645 (Electronic) 0002-9637 (Linking).

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Lin, D H; Lucas, E; Murimi, I B; Jackson, K; Baier, M; Frattaroli, S; Gielen, A C; Moyo, P; Simoni-Wastila, L; Alexander, G C

Physician attitudes and experiences with Maryland's prescription drug monitoring program (PDMP) (Journal Article)

Addiction, 112 (2), pp. 311-319, 2017, ISSN: 1360-0443 (Electronic) 0965-2140 (Linking).

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Lin, D H; Lucas, E; Murimi, I B; Kolodny, A; Alexander, G C

Financial Conflicts of Interest and the Centers for Disease Control and Prevention's 2016 Guideline for Prescribing Opioids for Chronic Pain (Journal Article)

JAMA Intern Med, 2017, ISSN: 2168-6114 (Electronic) 2168-6106 (Linking).

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904 entries « 1 of 46 »