If none of the categories below fits your request, we’re happy to discuss with you and connect you with the best resources here at UK for your interests.

Service providers

• James Aaron: CCTS Biomedical informatics core
• Dr. Daniel Harris: CCTS Biomedical informatics core
• Dr. Jin Chen: Medical informatics
• Dr. Hunter Moseley: Bioinformatics and systems biology
• Dr. V. K. Cody Bumgardner: Pathology informatics

Knowledge representation and data integration consultations

Advancements in biomedical research require the sharing of datasets, integration of disparate datasets, and access to shared knowledge frameworks. Therefore, it is important that biomedical knowledge is encoded in ways that are semantically precise, standardized, and computable. Our research topics include integration of biomedical terminologies using biomedical ontologies, construction of disease-specific knowledge maps, data visualization, and the development of user interfaces to support interacting with ontologies.

Qualitative research design

• Design of information artifacts and services (e.g. focus groups and interviews), usability testing
• Design of technology-mediated behavioral interventions

Biomedical knowledge map

• Integrate biomedical terminologies using disease-related ontologies such as UMLS, SNOMED CT, OMIM, and MeSH
• Development of ontologies and terminologies using domain knowledge and EHR data

Service providers

• Dr. Daniel Harris: ontology management, integration of ontologies for clinical research
• Dr. Sujin Kim: patient literacy analysis; design of behavioral interventions in diverse health care processes and patient outcomes
• Dr. Jin Chen: development of data-driven ontologies and terminologies
• Dr. Hunter Moseley: utilization of Gene Ontology in omics data analyses
• Dr. V. K. Cody Bumgardner: development of streaming semantic encoding of raw data sources and multi-stream and multi-ontology event correlation and processing

When providing healthcare services to patients, healthcare workers must retrieve previous information and document new information. Clinical informatics is the study of methods to improve this information workflow, including the capture and management of clinical information and the engineering of clinical decision support systems. Clinical research informatics is the use of informatics to enable the generation of new information about health and disease.

Clinical data collection to support clinical trials

• patient cohort identification

Secondary use of clinical data

• Patient cohort data management and storage
• Patient data de-identification
• Data transformation and pre-processing
• Application of machine learning and statistical tools

Service providers

• Dr. Daniel Harris: health analytics and learning networks, multi-site patient cohort identification
• Dr. Ramakanth Kavuluru: Longitudinal predictive modeling and association rule mining from EMRs.
• Dr. Jin Chen: temporal EHR data analysis using machine learning, medical image data analysis
• Dr. Qiang Cheng: biomarker and risk factor determination, patient time trajectory and fate prediction, subgroup identification, association or causal analysis, integrative study of heterogeneous data, clinical image analysis, EEG or other sig-nal analysis, and information management
• Dr. V. K. Cody Bumgardner: secure management and analysis of many types of pathology and laboratory data including, but not limited to, Next Generation Sequencing (NGS), Whole Slide Imaging (WSI), and clinical Mass Spectrometry (MS), which includes the curation of research data derived from clinical work-flows

Biomedical information is often captured in clinical notes or literatures in natural human language (instead of using structured and standardized formats). The field of information retrieval is concerned with identifying documents within a large collection that are most relevant to a user’s search. We provide consultations for research utilizing natural language processing (NLP) or text mining methods to analyze and understand the information within natural language documents.

Medical/biological literature based extraction

• Extraction of published evidences from medical or biological literatures (e.g., protein interactions, drug-disease treatment or preventative relations)

Clinical information extraction and retrieval

• Extraction of coded information from unstructured narratives (e.g., ejection fraction)
• Human-computer information retrieval using interactive text visualization

Service providers

• Dr. Daniel Harris: applied natural language processing for clinical data warehousing
• Dr. Ramakanth Kavuluru: extracting strong predictive signal by merging both structured and unstructured data sources from EMRs, scientific literature, and social media
• Dr. Sujin Kim: analyzing large corpus of electronic medical notes using conventional NLP tools

We provide consultations in public health informatics, which is the application of informatics at the level of populations to study health-related issues. Specific topics of study include the epidemiology of cancer and use of pharmaceuticals.

Service providers

• Dr. Ramakanth Kavuluru: - Mine social network messages (e.g., Twitter, Reddit) and blog posts for health-related insights (e.g., drug side effects, mental health disclosures, and estimates of prevalence)
• Dr. V. K. Cody Bumgardner: Population-scale monitoring, measurement, and reporting of distributed data sources from the real-time acquisition of data from mobile wearable devices, to the development and cloud-based operation of large data generators such as medical imaging and genomic sequencing devices.

Human-information interaction consultations

The purpose of biomedical informatics is to help people understand biomedical data and information, so studying how people interact with information is an essential component of this discipline. Areas of work include health literacy and information-seeking behaviors of healthcare professionals.

Service providers

• Dr. Daniel Harris: large-scale insurance claims databases and analysis, HIPAA-compliant geospatial informatics
• Dr. Sujin Kim: patient literacy analysis; design of behavioral interventions in diverse health care processes and patient outcomes.

Modern techniques for analyzing biological specimens produce large amounts of data describing gene expression, genome sequences, molecular structures, and molecular interactions. We provide consultations on bioinformatics and computational biology, which utilizes computational tools to manage and analyze biological data, leading to better understanding of living systems ultimately improving human health.

High-throughput omics data analysis

• DNAseq data processing and analysis
• RNAseq data processing and analysis
• Non-coding RNA data processing and analysis
• Proteomics data analysis
• Metabolomics data analysis

Differential expression and abundance analyses

• Abundance analysis on epigenomics, genomics, transcriptomics, proteomics, and especially metabolomics data

Single cell analysis

• Single-cell RNAseq cell trajectory analysis

Structural biology and computational drug discovery

• Protein modeling and simulations
• Virtual high-throughput drug binding screens

Service providers

• Dr. Hunter Moseley: a range of omics data analyses, especially metabolomics data analyses
• Dr. Jin Chen: RNAseq, microRNAseq, single-cell RNAseq, gene enrichment test
• Dr. Sally Ellingson: Structural biology and computational drug discovery
• Dr. Cody Bumgardner: secure data collection, processing, and reporting of omic pipelines using multi-cloud operations in clinical and research settings
• Dr. Qiang Cheng: DNAseq data analysis

We provide a range of computational and systems biology consultations, ranging from utilizing reaction maps to reveal interesting results in your sequencing data to utilizing interaction networks derived from public repositories.

Interaction network analysis

• Analyze interaction networks using molecular interactions derived from public repositories
• Construction of relevant interaction networks using gene expression data

Function and annotation enrichment analyses

• Gene set enrichment analysis
• Differential expression enrichment analysis
• Annotation enrichment analysis

Structural bioinformatics analysis

• 3D macromolecular structure analysis and modeling
• Molecular docking

Service providers

• Dr. Hunter Moseley: interaction network analysis, annotation enrichment analysis, combined analyses.
• Dr. Jin Chen: Network biology
• Dr. Sally Ellingson: molecular docking