A5041461031- Bioinformatics and Genomic Networks
- Gene expression and cancer classification
- Suicide and Self-Harm Studies
- Scientific Computing and Data Management
- Gene Regulatory Network Analysis
- SARS-CoV-2 and COVID-19 Research
- Health disparities and outcomes
- Cancer Cells and Metastasis
- Research Data Management Practices
- Monoclonal and Polyclonal Antibodies Research
- Cancer Diagnosis and Treatment
- Genetic Associations and Epidemiology
- Cancer Research and Treatments
- Epigenetics and DNA Methylation
- Mental Health Research Topics
- Evolution and Genetic Dynamics
- Distributed and Parallel Computing Systems
- Pancreatic and Hepatic Oncology Research
- vaccines and immunoinformatics approaches
- Neuroscience and Neuropharmacology Research
- Computational Drug Discovery Methods
- Climate Change and Health Impacts
- Plant-Microbe Interactions and Immunity
- Greenhouse Technology and Climate Control
- Data-Driven Disease Surveillance
University of Tennessee at Knoxville
2019-2024
Oak Ridge National Laboratory
2019-2024
University of North Carolina at Chapel Hill
2022-2024
UNC Lineberger Comprehensive Cancer Center
2022
Skin is composed of diverse cell populations that cooperatively maintain homeostasis. Up-regulation the nuclear factor κB (NF-κB) pathway may lead to development chronic inflammatory disorders skin, but its role during early events remains unclear. Through analysis single-cell RNA sequencing data via iterative random forest leave one out prediction, an explainable artificial intelligence method, we identified immunoregulatory for a unique paired related homeobox-1 (Prx1) + fibroblast...
Abstract Background A mechanistic understanding of the spread SARS-CoV-2 and diligent tracking ongoing mutagenesis are key importance to plan robust strategies for confining its transmission. Large numbers available sequences their dates transmission provide an unprecedented opportunity analyze evolutionary adaptation in novel ways. Addition high-resolution structural information can reveal functional basis these processes at molecular level. Integrated systems biology-directed analyses data...
Abstract We present an ensemble transfer learning method to predict suicide from Veterans Affairs (VA) electronic medical records (EMR). A diverse set of base models was trained a binary outcome constructed reported suicide, attempt, and overdose diagnoses with varying choices study design prediction methodology. Each model used twenty cross-sectional 190 longitudinal variables observed in eight time intervals covering 7.5 years prior the prediction. Ensembles seven were created fine-tuned...
Gene-to-gene networks, such as Gene Regulatory Networks (GRN) and Predictive Expression (PEN) capture relationships between genes are beneficial for use in downstream biological analyses. There exists multiple network inference tools to produce these gene-to-gene networks from matrices of gene expression data. Random Forest-Leave One Out Prediction (RF-LOOP) is a method that has been shown be efficient at producing frequently known GEne Network Inference with Ensemble trees (GENIE3). Here we...
As time progresses and technology improves, biological data sets are continuously increasing in size. New methods new implementations of existing needed to keep pace with this increase. In paper, we present a high-performance computing (HPC)-capable implementation Iterative Random Forest (iRF). This enables the explainable-AI eQTL analysis SNP over million SNPs. Using implementation, also method, iRF Leave One Out Prediction (iRF-LOOP), for creation Predictive Expression Networks on order...
Abstract Leveraging the use of multiplex multi-omic networks, key insights into genetic and epigenetic mechanisms supporting biofuel production have been uncovered. Here, we introduce RWRtoolkit, a generation, exploration, statistical package built for R command line users. RWRtoolkit enables efficient exploration large highly complex biological networks generated from custom experimental data and/or publicly available datasets, is species agnostic. A range functions can be used to find...
This study quantified eight, small molecule neurotransmitters collected simultaneously from prefrontal cortex of C57BL/6J mouse (n=23) during wakefulness and isoflurane anesthesia (1.3%). Using as an independent variable enabled evaluation the hypothesis that differentially alters concentrations multiple their interactions. Machine learning was applied to reveal higher order interactions among neurotransmitters. a between-subjects design, microdialysis performed anesthesia. Concentrations...
The FAIR principles of open science (Findable, Accessible, Interoperable, and Reusable) have had transformative effects on modern large-scale computational science. In particular, they encouraged more access to use data, an important consideration as collaboration among teams researchers accelerates the workflows by those solve problems increases. How best apply themselves, software generally, is not yet well understood. We argue that engineering concept technical debt management provides a...
Abstract The SARS-CoV-2 pandemic recently entered an alarming new phase with the emergence of variants concern (VOC) and understanding their biology is paramount to predicting future ones. Current efforts mainly focus on mutations in spike glycoprotein (S), but changes other regions viral proteome are likely key. We analyzed more than 900,000 genomes a computational systems approach including haplotype network protein structural analyses reveal lineage-defining critical functional...
Despite a recent global decrease in suicide rates, death by has increased the United States. It is therefore imperative to identify risk factors associated with attempts combat this growing epidemic. In study, we aim potential of attempt using geospatial features an Artificial intelligence framework.
Abstract Cancer-associated fibroblast (CAF) subpopulations in pancreatic ductal adenocarcinoma (PDAC) have been identified using single-cell RNA sequencing (scRNAseq) with divergent characteristics, but their clinical relevance remains unclear. We translate scRNAseq-derived CAF cell-subpopulation-specific marker genes to bulk RNAseq data, and develop a single- sample classifier, DeCAF, for the classification of clinically rest raining perm issive subtypes. validate DeCAF 19 independent...
Genome-wide association studies (GWAS) identify genetic variants underlying complex traits but are limited by stringent genome-wide significance thresholds. We present GRIN (Gene set Refinement through Interacting Networks), which increases confidence in the expanded gene retaining genes strongly connected biological networks when GWAS thresholds relaxed. was validated on both simulated interrelated sets as well multiple traits. From summary statistics of suicide attempt, a phenotype,...
For plants, distinguishing between mutualistic and pathogenic microbes is a matter of survival. All contain microbe-associated molecular patterns (MAMPs) that are perceived by plant pattern recognition receptors (PRRs). Lysin motif receptor-like kinases (LysM-RLKs) PRRs attuned for binding triggering response to specific MAMPs, including chitin oligomers (COs) in fungi, lipo-chitooligosaccharides (LCOs), which produced mycorrhizal fungi nitrogen-fixing rhizobial bacteria, peptidoglycan...
As time progresses and technology improves, biological data sets are continuously increasing in size. New methods new implementations of existing needed to keep pace with this increase. In paper, we present a high performance computing(HPC)-capable implementation Iterative Random Forest (iRF). This enables the explainable-AI eQTL analysis SNP over million SNPs. Using also method, iRF Leave One Out Prediction (iRF-LOOP), for creation Predictive Expression Networks on order 40,000 genes or...
Abstract Genome-wide association studies (GWAS) identify genetic variants underlying complex traits but are limited by stringent genome-wide significance thresholds. Here we dramatically relax GWAS stringency orders of magnitude and apply GRIN (Gene set Refinement through Interacting Networks), which increases confidence in the expanded gene retaining genes strongly connected biological networks from diverse lines evidence. From multiple summary statistics suicide attempt, a psychiatric...
Abstract Introduction. Alternatively spliced tissue factor (asTF) promotes progression of pancreatic ductal adenocarcinoma (PDAC) via activating b1-integrins on PDAC cell surfaces. hRabMab1, a humanized inhibitory anti-asTF antibody we recently developed, can suppress primary tumor growth as single agent. Whether hRabMab1 has the potential to metastases in is unknown. Aim. To test hRabMab1’s ability metastatic spread combination with chemotherapy. Methods. asTF-proficient, KRAS G12V-mutant...
Alternatively spliced tissue factor (asTF) promotes the progression of pancreatic ductal adenocarcinoma (PDAC) by activating β1-integrins on PDAC cell surfaces. hRabMab1, a first-in-class humanized inhibitory anti-asTF antibody we recently developed, can suppress primary tumor growth as single agent. Whether hRabMab1 has potential to metastases in is unknown. Following vivo screening three asTF-proficient human lines, chose make use KRAS G12V-mutant line PaCa-44, which yields aggressive...
Abstract Cancer-associated fibroblasts (CAFs) in pancreatic adenocarcinoma (PDAC) are known to play a significant role regulating tumor progression, invasion, and metastasis. Multiple studies using experimental strategies, as well single-cell RNA-sequencing (scRNAseq) technology, have shown the existence of subpopulations PDAC CAFs, with divergent physical biological characteristics. However, how these CAF translate clinical practice remains unclear. Using combination sc- bulk RNAseq data,...
Objective: To assess the utility of tumor-intrinsic and cancer-associated fibroblast (CAF) subtypes pancreatic ductal adenocarcinoma (PDAC) in predicting response to neoadjuvant therapy (NAT) overall survival (OS). Background: PDAC remains a deadly disease with limited treatment options, both tumor as well microenvironment play an important role pathogenesis. Gene expression–based (classical basal-like) have been shown predict outcomes, but are still evolving. Methods: RNA-sequencing was...
Abstract Currently, it remains unclear how the knowledge of cancer-associated fibroblast (CAF) subtypes in pancreatic adenocarcinoma (PDAC) may apply to patients. Using a combination sc- and bulk RNAseq methods, we present two CAF with permissive (permCAF) restraining (restCAF) characteristics patients that can be classified by clinically usable single-sample classifier, DeCAF. DeCAF was trained 4 independent datasets using penalized logistic regression validated 7 high reproducibility...
Abstract Despite a global decrease in suicide rates recent years, death by has increased the United States. It is therefore imperative to identify risk factors associated with attempts order combat this growing epidemic. In study, we use an explainable-artificial intelligence method, iterative Random Forest, predict using data from Million Veteran Program. Our predictive model incorporates multiple environmental variables (e.g., elevation, light wavelength absorbance, temperature, humidity,...