Genetics and Genomics Commons^™

Dissecting The Etiology Of Alcohol Use Disorder By An Integrative Heritable Component Approach, Ivy Garrenton

Computer Science Theses & Dissertations

Alcohol Use Disorder (AUD) is a pervasive condition characterized by complex interplay among genetic, phenotypic, and environmental factors. Although previous studies have identi fied genetic loci associated with alcohol consumption, these efforts have not captured the genetic heterogeneity and gene-environment interactions underlying AUD pathogenesis. To address this critical gap, we developed a novel statistical methodology that integrates phenotypic, genotypic, and environmental data through an environmentally modified Genetic Relationship Matrix (GRM) to derive AUD-related traits with enhanced heritability.

This approach demonstrated superior performance in both simulated and real-world datasets. Traits derived using the environmentally modified GRM exhibited significantly higher estimated heritability …

Identifying Relevant Covariates In Rna-Seq Analysis By Pseudo-Variable Augmentation, Yet Nguyen, Dan Nettleton

Mathematics & Statistics Faculty Publications

RNA-sequencing (RNA-seq) technology allows for the identification of differentially expressed genes, which are genes whose mean transcript abundance levels vary across conditions. In practice, RNA-seq datasets often include covariates that are of primary interest in addition to a set of covariates that are subject to selection. Some of these covariates may be relevant to gene expression levels, while others may be irrelevant. Ignoring relevant covariates or attempting to adjust for the effect of irrelevant covariates can compromise the identification of differentially expressed genes. To address this issue, we propose a variable selection method that uses pseudo-variables to control the expected …

Integrating Genetic Modifier Genotype With Serum Proteomics In Duchenne Muscular Dystrophy Clinical Trials Links Ltbp4 Genetic Modifier To Il-23/Cd93 Pathways In Muscle, Utkarsh J. Dang, Yuan Fang, Daniele Sabbatini, Elena Pegoraro, Luca Bello, Paula R. Clemens, Michela Guglieri, John Van Den Anker, Jesse Damsker, Laura Hagerty, Yetrib Hathout, Michael Ziemba, Lauren Morgenroth, Surajit Bhattacharya, Kanneboyina Nagaraju, Jyoti K. Jaiswal, Eric P. Hoffman

Mathematics & Statistics Faculty Publications

Genetic modifiers of Duchenne muscular dystrophy (DMD) that alter disease severity or response to therapy have been reported using natural history or registry data sets of older corticosteroid-treated patients. We tested associations of genetic modifiers on motor function outcomes in young (4 to <  7 years) steroid naïve clinical trial participants. Participants in clinical trials (VBP15-002/003 [n = 48]; VBP15-004 [n = 121]; DNA available for n = 110) were genotyped for eight published genetic modifier loci, and associations of genotypes with baseline motor function defined via an age-adjusted linear model. Corticosteroid drug response was modeled by genotype-stratified placebo vs. steroid treatment at 12- and 24-weeks posttreatment (mixed model for repeated measures). …

Metabolic Reprogramming Following Mitochondrial Transfer Between Idh2-Mutant Chondrosarcoma Cells And A Normal B-Cell Line, Caleb Wyckoff, Christopher Osgood, Ellen Jing, Michael Stacey

Bioelectrics Publications

Background/Objectives: Chondrosarcoma, glioblastoma, acute myeloid leukemia, chronic lymphocytic leukemia, and cholangiocarcinoma cancers all contain mutations in the gene isocitrate dehydrogenase 2 (IDH2). The mutant IDH2 enzyme metabolizes alpha-ketoglutarate (αKG) into the potent oncometabolite D-2-hydroxyglutarate (D2HG) in the mitochondria of these cancers, leading to altered cellular metabolism. Emerging evidence suggests that mitochondrial transfer between cancer and recipient cells represents an important form of intercellular communication that may influence cellular metabolism. The presence of intercellular TNTs between IDH2-mutant chondrosarcoma cells motivated an investigation into mitochondria-associated physiological changes occurring during an intercellular exchange with immune cells. A mitochondrial transfer is a two-way …

35 Individuals With Huwe1-Related Neurodevelopmental Disorder And Suggested Clinical Evaluations, Mindy H. Li, Deziree L. Coleman, Kelsey Hogan, Danielle Luz, Lindsay Bhandari, Newell Belnap, Tiffany Busa, Charles Coutton, Klaus Dieterich, Svetlana Gorokhova, Clara Hildebrandt, Rachel Logan, Milena Mariani, Manuela Morleo, Vincenzo Nigro, John Pappas, Rachel Rabin, Kelly Schoch, Angelo Selicorni, Vandana Shashi, Rebecca Spillman, Jennifer Sullivan, Charlotte Tardy, Samantha A. Schrier Vergano, Brock Grill, Kristin Baranano

Department of Pediatrics Faculty Publications

HUWE1 (HECT, UBA, and WWE Domain Containing E3 Ubiquitin Protein Ligase1, OMIM 300697), located at Xp11.22, encodes a ubiquitin ligase that is highly conserved across species. Genetic variants in HUWE1 described in multiple independent studies cause X-linked intellectual disability, including in the patients identified by Juberg, Marsidi, and Brooks. This report describes 35 additional cases of individuals with variants in HUWE1 and suggested guidelines for clinical management. Our study includes several female cases, which have not been widely reported previously. Our findings confirm earlier reported clinical features including developmental delay, autism, hypotonia, short stature, and dysmorphic facial features as well …

The Rna-Binding Protein Pumilio Limits Polymodal Noiception In Drosophila Larvae, Sara Palega, Hannah Davenport, Rebeccah K. Stewart, Jessica Horton, Andrew Bellemer

Microbiology & Molecular Cell Biology Faculty Publications

Nociception is the process by which the nervous system detects and processes information about potentially harmful environmental stimuli to generate behavioral and physiological responses. The process of nociception undergoes plasticity in response to injury, inflammation, and infection to shape the sensitivity of nociceptive circuits and the behavioral responses they control. We are increasingly aware that post-transcriptional regulation of gene expression shapes the sensitivity and plasticity of nociceptive sensory neurons and nociceptive behavior. In Drosophila, the Pumilio RNA-binding protein interacts with diverse target mRNAs to regulate their abundance and translation in a wide range of contexts including the establishment of …

An Ensemble Classifier For Ordinal Outcomes In High-Dimensional Genomics Data, Heranga K. Rathnasekara, Sinjini Sikdar

Mathematics & Statistics Faculty Publications

Analysis of genomics data for predicting disease outcomes is a fast-growing field in medical research. There often exist categorical, specifically, ordinal outcomes that need to be predicted based on genomic profiles. This has led to recent development of some high-dimensional ordinal classification methods that can address the large dimensionality of the genomic covariate set. These high-dimensional ordinal models tend to vary widely in their performance depending on the data they are applied to and the evaluation criteria used. In this article, we outline an ensemble ordinal classifier that integrates different ordinal modeling approaches through bootstrap-based model evaluation, multi-metric performance assessment, …

Mitochondrial Genome Of The Indo-Pacific Mesophotic Coral Leptoseris Columna (Scleractinia: Agariciidae) Assembled Using Pacbio Long-Read Sequencing, Nomita Rani Adhikary, Daniel J. Barshis, J. Antonio Baeza

Biological Sciences Faculty Publications

Leptoseris columna, a mesophotic coral species belonging to the family Agariciidae, is distributed throughout the Indo-Pacific region. This species is considered as of "Least concern" by the IUCN, yet, faces multiple local and global stressors. To support conservation plans, this study sequenced and characterized the complete mitochondrial genome of L. columna. The complete mitochondrial genome of Leptoseris columna was assembled using PacBio long-reads with a coverage of 459× per bp. The AT-rich mitochondrial genome of Leptoseris columna is 18,546 bp long and comprises 13 protein-coding genes (PCGs), 2 transfer RNA genes (trnM and trnW), and 2 ribosomal RNA …

Larval Genomics As A Viable, Fisheries-Independent Tool For Investigating Population Structure In Tropical Pacific Tunas, Jacob E. Jaskiel, Hannah E. Aichelman, Giulia Anderson, Louw Claassens, James E. Fifer, Christina M. Hernandez, Alexa K. Huzar, Joel K. Llopiz, Jan W. Witting, Sean P. Mullen, Randi D. Rotjan

Biological Sciences Faculty Publications

Understanding how dispersal, life history, and environmental variability shape genetic connectivity in the open ocean remains a central challenge in evolutionary biology. Highly migratory marine predators like tunas have traditionally been considered genetically homogeneous across ocean basins, yet emerging genomic evidence suggests that cryptic population structure can persist even in species with high gene flow and large effective population sizes. We used 2bRAD sequencing of 348 larval and subadult skipjack (Katsuwonus pelamis), yellowfin (Thunnus albacares), and bigeye tuna (T. obesus) collected from the central Pacific across 7 years of sampling to examine species boundaries, …

A Complete Diploid Human Genome Benchmark For Personalized Genomics, Nancy F. Hansen, Nathan Dwarshuis, Hyun Joo Ji, Arang Rhie, Hailey Loucks, Glennis A. Logsdon, Mitchell R. Vallger, Jessica M. Storer, Juhyun Kim, Eleni Adam, Nicolas Alternose, Dmitry Antipov, Mobin Asri, Sofia Barreira, Stephanie C. Bohaczuk, Andrey V. Bzikadze, Sara A. Carioscia, Andrew Carroll, Kuan-Hao Chao, Yanan Chu, Arun Das, Peter Ebert, Adam English, Mark Fleharty, Laura E. Fleming, Giulio Formenti, Andrea Guarracino, Gabrielle A. Hartley, Katharine Jenike, Jenna Kalleberg, Yu Kang, Robert King, Josipa Lipovac, Mira Mastoras, Matthew W. Mitchell, Shloka Negi, Nathan D. Olson, Keisuke K. Oshima, Luis F. Paulin, Brandon D. Pickett, David Porubsky, Jane Ranchalis, Desh Ranjan, Mikko Rautiainen, Harold Riethman, Robert D. Schnabel, Fritz J. Sedlazeck, Kishwar Shafin, Mile Sikic, Steven J. Solar, Alexander P. Sweeten, Winston Timp, Justin Wagner, Dongahn Yoo, Ying Zhou, Erik Garrison, Evan E. Eichler, Michaeel C. Schatz, Andrew B. Stergachis, Rachel J. O'Neill, Karen H. Miga, Steven L. Salzberg, Sergey Koren, Justin M. Zook, Adam M. Phillippy

School of Medical Diagnostics & Translational Sciences Publications

Human genome sequencing typically relies on mapping reads to a reference genome to call variants, but this approach introduces technical biases, excluding duplicated and structurally polymorphic regions of the genome. To overcome this, we present a telomere-to-telomere genome benchmark with near-perfect accuracy across 99.4% of the diploid HG002 genome. This benchmark adds 701.4 Mb of autosomal sequence and both sex chromosomes (216.8 Mb), which were absent from prior benchmarks. We annotated genes and repeats on both haplotypes, including 19,956 protein-coding genes on the maternal haplotype and 19,190 on the paternal haplotype, and developed new methods to measure the accuracy of …

Chromnet: A Multi-Task Learning Framework For Cross-Cell Type Prediction Of 3d Chromatin Interactions Using Epigenetic Signals, Bin Wang, Shaokai Wang, Liqing Ding, Hongdong Li, Yaohang Li, Jianxin Wang

Computer Science Faculty Publications

The 3D organization of chromatin plays a fundamental role in gene regulation, cellular function, and disease mechanisms. However, current experimental techniques, such as Hi-C, remain costly and labor-intensive, limiting their application in large-scale and disease-related studies. To address this challenge, ChromNet is presented, a multi-task learning framework that integrates epigenetic signals across diverse cell types to enable high-precision prediction of chromatin architecture. By incorporating noise perturbation and auxiliary classification tasks, ChromNet improves the identification of topologically associating domains (TADs) and cell-type-specific chromatin structures, demonstrating superior generalization performance. Notably, ChromNet accurately predicts chromatin interactions in acute myeloid leukemia (AML) samples by …

Attention-Based Multi-Omics Fusion For Drug Synergy Prediction, Kusal Debnath, Pratip Rana, Preetam Ghosh

Computer Science Faculty Publications

Drug combination therapy in disease management gained popularity in the last few decades. Computational modeling of such combinations is an active area of research in the drug discovery domain. While earlier approaches solely emphasized on the structural features of participating drugs for designing synergistic models, they lack other crucial factors directly linked with drug administration - omics expressions. As differential omics expression is a downstream consequence of the administered drug combinations, utilizing such expressions while designing synergistic models promises robust and dynamic modeling. In this work, we propose SynergyLM that fuses multi-omics features with drug embeddings to build an omics-aware …

From Molecules To Minds: Integrative Multi-Omics In Psychiatry, Hossein Abbasi, Sage E. Hawn, Arash Javanbakht, Soraya Seedat, Kyle Bourassa, Sinead M. Sinnott, Antonia V. Seligowski, Sian Hemmings, Nathan A. Kimbrel, Alicia K. Smith, Leslie Brick, Divya Mehta

Psychology Faculty Publications

Psychiatric disorders are biologically complex conditions arising from interactions across genomic, epigenomic, transcriptomic, proteomic, metabolomic, and metagenomic layers. Single-omics approaches rarely capture more than a fraction of the variance in complex conditions, underscoring the importance of integrative multi-omics frameworks. This mini-review summarizes key methodologies and their application in psychiatric research, with a focus on systems-level integration of genomic risk scores, transcriptomic networks, and neuroimaging data to advance biological understanding of disorders such as depression, schizophrenia, and Alzheimer’s disease. We also outline the infrastructural requirements for effective multi-omics research, including standardized biobanking, Laboratory Information Management Systems, adherence to FAIR data principles, …

Comparative Analysis Of Six New Chloroplast Genomes In Platanthera (Orchidaceae) Enhances Understanding Of Its Diversification, Lisa E. Wallace, Martin I. Batalla, Matthew Maisonave

Biological Sciences Faculty Publications

Platanthera is among the most diverse genera of orchids in north temperate regions, with high species diversity in Asia and North America. Despite many ecological studies in this group, little is known about its genomic diversity. Here, we report the newly annotated chloroplast genomes from six species in subgenus Limnorchis from North America and compare them with plastomes published for Platanthera species from Asia and Europe. We found that the plastomes of species in subg. Limnorchis are among the smallest reported for Platanthera thus far. While major structural differences were not detected in the newly sequenced species, ndh genes were …

Acute Fatty Liver Of Pregnancy And Fetal Fatty Acid Oxidation Disorders: A Systematic Review, Dante Varotsis, Sarah Araji, Rebecca Horgan, Jennifer E. Powel, Rodney Mclaren Jr., Brian Kirmse, Mona Makhamreh, Huda B. Al-Kouatly

Department of Obstetrics & Gynecology Faculty Publications

OBJECTIVE:

To evaluate the association between maternal acute fatty liver of pregnancy (AFLP) and fetal fatty acid oxidation (FAO) disorders and to define the clinical and genetic characteristics of mothers with AFLP and their fetuses affected by FAO disorders, we performed a systematic literature review of all reported cases of AFLP that underwent genetic testing for FAO disorders.

DATA SOURCES:

We searched PubMed, Ovid MEDLINE, Cochrane Library, CINAHL (EBSCO), Scopus, and ClinicalTrials.gov. Terms included were related to AFLP and FAO testing.

METHODS OF STUDY SELECTION:

We conducted a systematic literature review from inception through May 18, 2025, to evaluate the …

Microarray Analysis Of Human Abdominal Aortic Aneurysm With Emphasis On Cardiovascular Genes Revealed Differentially Expressed Genes, Song Lu, Li Ping Li, John V. White, Xiaoying Zhang, Ifeyinwa Nwaneshiudu, Adaobi Nwaneshiudu, Nectaria Ntaoula, John Gaughan, Dimitri S. Monos, Wan-Lu Lin, Charalambos C. Solomides, Emilia L. Oleszak, Chris D. Platsoucas

Biological Sciences Faculty Publications

Background/Aim: We examined gene expression profiles in abdominal aortic aneurysm (AAA) lesions vs. normal aortas by cDNA microarray and real-time quantitative reverse-transcriptase polymerase chain reaction (qRT-PCR).

Materials and Methods: Phosphorus (32P)-labeled cDNA from AAA specimens (mean AAA size 6.65 cm) and normal aortas were hybridized with a 588-gene microarray primarily of the cardiovascular system. The results were validated by qRT-PCR.

Results: A total of 35 out of the 588 genes were differentially expressed, with either log2 ratio of AAAs/controls ≥1 (upregulated; 20 genes) or ≤−1 (downregulated; 15 genes) in AAA lesions vs. normal aorta, and 25 of these were significantly …

Rapid Urbanization Reduces Genetic Diversity And Increases Genetic Differentiation Of A Lynx Spider Oxyopes Sertatus In Central Taiwan, Ying-Yuan Lo, Chi Wei, Wan-Jyun Chen, Chung-Ping Lin

Biological Sciences Faculty Publications

Urbanization is a dominant force driving destructive and irreversible changes of natural habitats in modern times. While the effects of urbanization on community composition and phenotypic responses are well-documented, its influence on genetic diversity and population structure remains understudied, particularly for invertebrates in subtropical regions. This study tested the hypothesis that urbanization reduces genetic diversity and increases population differentiation in the lynx spider Oxyopes sertatus, a common foliage-dwelling spider in Taiwan. We sampled 245 individuals from 17 sites distributed along an urban-rural gradient and quantified urbanization intensity using land-use composition at both landscape (4 km²) and local (0.25 km²) …

Privacy-Preserving Federated Learning With Optimized Ensemble Weighting And Knowledge Distillation For Covid-19 Detection From Non-Iid Medical Imaging Data, Richard Annan, Hong Qin, Robert Newman, Madhuri Siddula, Letu Qingge

Computer Science Faculty Publications

Medical imaging enables rapid and accurate diagnosis of COVID-19, with CT scans proving especially effective. However, data privacy concerns limit collaborative model development across hospitals. To address this issue, we introduce a novel federated learning framework. It is referred to as Independent Knowledge Distillation with post-Ensemble Federated Learning (IKDEFL). Differential Privacy (DP) is integrated into the framework to improve privacy guarantees. Three DP mechanisms are evaluated. These include Fixed Gaussian, Gaussian Adaptive, and Tree Adaptive. The evaluation has been conducted on heterogeneous and Non-Independent and Identically Distributed (Non-IID) datasets. These datasets reflect real-world hospital scenarios. Results show that IKDEFL significantly …

Explainable Convolutional Neural Network Model Provides An Alternative Genome-Wide Association Perspective On Mutations In Sars-Cov-2, Parisa C. Hatami, Richard Annan, Luis Miranda, Jane L. Gorman, Mengjun Xie, Letu Qingge, Hong Qin

Computer Science Faculty Publications

Identifying informative genomic features in SARS-CoV-2 can help clarify patterns of viral evolution. In this study, we developed an explainable convolutional neural network (CNN) model to classify SARS-CoV-2 genomic sequences into the WHO-designated Variants of Concern (VOCs), Alpha, Beta, Gamma, Delta, and Omicron. Using a balanced dataset of genomes, the classification CNN achieved 99.96% accuracy on the held-out test set. To interpret the model’s predictions, we applied SHapley Additive exPlanations (SHAP) to estimate the contribution of each nucleotide position to VOC-label prediction and compared aggregated attributions with a chi-square GWAS baseline applied to the same categorical labels. SHAP prioritized several …

Physiologic Markers Of Mortality In Acute Valve Syndrome: An Ischemic Physiology Score Stratifies Patient Risk, Omar Saleh, Nicholas J. Valle, Israa Saleh, Raymond Benza, Deepak R. Talreja, Matthew R. Summers

Department of Medicine Faculty Publications

Background: Acute valve syndrome (AVS) represents a high-risk phenotype of advanced valvular disease with largely uncharacterized risk heterogeneity. We aimed to validate an expanded AVS definition and develop a physiology-dependent risk stratification tool using available clinical markers.

Methods: This retrospective study analyzed 2380 patients undergoing aortic valve replacement for severe aortic stenosis and classified them as AVS (n = 1556) or progressive valvular disease (n = 824). The primary outcome was 1-year all-cause mortality. An L2-regularized logistic regression model was developed to predict 1-year mortality using admission laboratory markers and comorbidity burden. Model performance was assessed using nested cross-validation with …

Covariate Selection For Rna-Seq Differential Expression Analysis With Hidden Factor Adjustment, Farzana Noorzahan, Hyeongseon Jeon, Yet Nguyen

Mathematics & Statistics Faculty Publications

In RNA-seq data analysis, a primary objective is the identification of differentially expressed genes, which are genes that exhibit varying expression levels across different conditions of interest. It is widely known that hidden factors, such as batch effects, can substantially influence the differential expression analysis. Furthermore, apart from the primary factor of interest and unforeseen artifacts, an RNA-seq experiment typically contains multiple measured covariates, some of which may significantly affect gene expression levels, while others may not. Existing methods either address the covariate selection or the unknown artifacts separately. In this study, we investigate two integrated strategies, FSR_sva and SVAall_FSR, …

Neuroinflammatory Signaling And Immune Cell Infiltration Differ In Brains Of Rats Exposed To Space Radiation And Social Isolation, Austin M. Adkins, Zachary N. M. Luyo, Alea F. Boden, Riley S. Heerbrandt, Richard A. Britten, Laurie L. Wellman, Larry D. Sanford

Center for Integrative Neuroscience and Inflammatory Diseases (CINID) Faculty Publications

Astronauts on the proposed Mars missions will be exposed to extended periods of social isolation (SI) and space radiation (SR). SI and SR-induced immune dysregulation can result in persistent neuroinflammation and neuronal damage which could negatively impact an astronaut’s health and ability to maintain adequate levels of performance. The synergistic effects of combined SI and SR on immune system functionality and the brain remain unknown. Determining how single and combined inflight stressors modulate the immune system is crucial for fully understanding pathways impacting astronaut health and performance. We used ground-based analogs of SI and SR in rodent models to investigate …

Lap-Hsp60 Complex Modulates Epithelial Tight Junction Barrier, Arun Bhunia, Manalee Manalee Samaddar, Chen Sun, Nicholas Gallina, Nicole Irizarry-Tardi, Donqi Liu, Shivendra Tenguria, Rishi Drolia, Anika Jain, Daisuke Kihara, Wen Jiang, Kee-Hong Kim, Abigail Cox, Kurt Ristroph, Gregory Knipp, Nicholas Noinaj

Biological Sciences Faculty Publications

During infection, Listeria adhesion protein (LAP), a housekeeping enzyme, acts as a tight junction modulator (TJM) through interaction with Hsp60 to facilitate Listeria monocytogenes translocation across the intestinal epithelial barrier. Here, we used purified LAP as a potential TJM to overcome the limiting and variable effects observed by other agents in the class. We structurally determined the LAP interaction alone and in complex with Hsp60 utilizing cryo-EM and computational analysis. LAP structure resolved at 2.83 Å, forms multimeric interlocking dimers and tetramers, and the N-domain interacts with Hsp60, while the C-domain bridges the bacterial surface receptor InlB. The structural studies …

Mobula, Bioinspiration, Filter Feeding, Form And Function, J. B. Teeple, S. R. Kahane-Rapport, K. E. Cohen, L. Hamann, J. A. Strother, E. W.M. Paig-Tran

Biological Sciences Faculty Publications

Mobulas (manta and devil rays) are large-scale ram filter feeders that separate planktonic food particles from large volumes of water with minimal clogging. This contrasts with most human-made filters that can suffer from problematic clogging requiring additional mechanisms for clearing blocked surfaces and maintaining performance. Prior studies have shown that mobulas employ a unique mechanism referred to as ricochet separation to filter feed, whereby captive vortices in filter pores cause particles to bounce off the filter surfaces and away from the filter pores. This mechanism enables the filtration of particles smaller than the pore size and reduced clogging. However, few …

Multi-Locas Gwas Mapping And Candidate Gene Analysis Of Anticancer Peptide Lunasin In Soybean (Glycine Max L. Merr), Rikki Locklear, Jennifer Kusumah, Layla Rashad, Felicia Lugaro, Sonia Viera, Nathan Kipyego, Faith Kipkosgei, Daisy Jerop, Shirley Jacquet, Mythy Addelmajid Kassem, Jiazheng Yuan, Elvira De Mejia, Rouf Mian

Biological Sciences Faculty Publications

Soybean (Glycine max) peptide lunasin exhibits significant cancer-preventive, antioxidant, and hypocholesterolemic effects. This study aimed to identify quantitative trait nucleotides (QTNs) associated with lunasin content and to annotate the candidate genes in the soybean genome. The mapping panel of 144 accessions was gathered from the USDA Soybean Germplasm Collection, encompassing diverse geographical origins and genetic backgrounds, and was genotyped using SoySNP50K iSelect Beadchips. The lunasin content in soybean seeds was measured using the enzyme-linked immunosorbent assay (ELISA) method, with lipid-adjusted soybean flour prepared from seeds obtained from the Germplasm Resource Information Network (GRIN) of USDA-ARS in 2003 and …

Copula-Based Bayesian Model For Detecting Differential Gene Expression, Prasansha Liyanaarachchi, N. Rao Chaganty

Mathematics & Statistics Faculty Publications

Deoxyribonucleic acid, more commonly known as DNA, is a fundamental genetic material in all living organisms, containing thousands of genes, but only a subset exhibit differential expression and play a crucial role in diseases. Microarray technology has revolutionized the study of gene expression, with two primary types available for expression analysis: spotted cDNA arrays and oligonucleotide arrays. This research focuses on the statistical analysis of data from spotted cDNA microarrays. Numerous models have been developed to identify differentially expressed genes based on the red and green fluorescence intensities measured using these arrays. We propose a novel approach using a Gaussian …

Foundation Models In Bioinformatics, Fei Guo, Renchu Guan, Yaohang Li, Qi Liu, Xiaowo Wang, Can Yang, Jianxin Wang

Computer Science Faculty Publications

With the adoption of foundation models (FMs), artificial intelligence (AI) has become increasingly significant in bioinformatics and has successfully addressed many historical challenges, such as pre-training frameworks, model evaluation and interpretability. FMs demonstrate notable proficiency in managing large-scale, unlabeled datasets, because experimental procedures are costly and labor intensive. In various downstream tasks, FMs have consistently achieved noteworthy results, demonstrating high levels of accuracy in representing biological entities. A new era in computational biology has been ushered in by the application of FMs, focusing on both general and specific biological issues. In this review, we introduce recent advancements in bioinformatics FMs …

Gramseq-Dta: A Grammar-Based Drug-Target Affinity Prediction Approach Fusing Gene Expression Information, Kasul Debnath, Pratip Rana, Preetam Ghosh

Computer Science Faculty Publications

Drug–target affinity (DTA) prediction is a critical aspect of drug discovery. The meaningful representation of drugs and targets is crucial for accurate prediction. Using 1D string-based representations for drugs and targets is a common approach that has demonstrated good results in drug–target affinity prediction. However, these approach lacks information on the relative position of the atoms and bonds. To address this limitation, graph-based representations have been used to some extent. However, solely considering the structural aspect of drugs and targets may be insufficient for accurate DTA prediction. Integrating the functional aspect of these drugs at the genetic level can enhance …

A Data-Driven Sliding-Window Pairwise Comparative Approach For The Estimation Of Transmission Fitness Of Sars-Cov-2 Variants And The Construction Of The Evolution Fitness Landscape, Md Jubair Pantho, Richard Annan, Landen Alexander Bauder, Sophia Huang, Letu Qingge, Hong Qin

Computer Science Faculty Publications

Estimating the transmission fitness of SARS-CoV-2 variants and understanding their evolutionary fitness trends are important for epidemiological forecasting. Existing methods are often constrained by their parametric natures and do not satisfactorily align with the observations during COVID-19. Here, we introduce a sliding-window data-driven pairwise comparison method, the differential population growth rate (DPGR) that uses viral strains as internal controls to mitigate sampling biases. DPGR is applicable in time windows in which the logarithmic ratio of two variant subpopulations is approximately linear. We apply DPGR to genomic surveillance data and focus on variants of concern (VOCs) in multiple countries and regions. …

Benchmarking Batch-Effect Correction Methods Towards The Construction Of A Triple-Negative Breast Cancer Cell Atlas, Peter Scheible, Amy H. Tang, Jing He, Jiangwen Sun

Computer Science Faculty Publications

Triple-negative breast cancer (TNBC) requires detailed cellular mapping given its aggressive nature, immense tumor heterogeneity and genetic diversity. We integrated 156,794 cells from six scRNA-seq datasets—including tumors, metastases, and cell lines—to build a TNBC scRNA cell atlas, focusing on batch effect mitigation while maintaining biological and molecular details. Preprocessing f ilters noise, normalizes data, and leverages PCA for integration readiness. We utilized scANVI, a semi-supervised tool, to align datasets, preserving TNBC’s complex tumor heterogeneity via marker annotations [1]. UMAPs demonstrate biological clustering in integrated data, contrasted with datasetdriven unintegrated patterns. Assessments verifying effective batch correction. This method aligns with NASA’s …