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Competitive qTMDD: Exact Formula of Total Quasi-Steady State Approximation in Competitive Target-Mediated Drug Disposition

Computational Biology and Bioinformatics

Competitive target-mediated drug disposition (competitive TMDD) has been used to describe the behavior of two different types of ligands competing for a common receptor. Due to the complexit…

Computational Approach to Identify Potential Inhibitory Molecule Against Bacterial Enzyme

Computational Biology and Bioinformatics

This study aimed to identify potential inhibitors of meso-diaminopimelate decarboxylase (LYASE), a bacterial enzyme crucial for lysine biosynthesis, using molecular docking simulations. The…

Computational Modeling of Bispecific Antibodies Targeting CD30+ Cells in Hodgkin Lymphoma and Anaplastic Large Cell Lymphoma

Computational Biology and Bioinformatics Fourth Award

Every year, approximately 90,000 people in the United States are diagnosed with lymphoma, a cancer impacting white blood cells called lymphocytes. The CD30 receptor, overexpressed in Hodgkin…

Computational Prediction of Nonabine as a Novel Cannabinoid Receptor Subtype 2 Selective Agonist

Computational Biology and Bioinformatics

Cannabinoid receptor subtype 2 (CB2), a G protein-coupled receptor within the endocannabinoid system (ECS), has shown promise as a therapeutic target in cancer and inflammatory diseases due…

Cracking the Seizure Code: A Deep Learning Approach to Neonatal Seizure Detection Utilizing Hybrid Architecture for Multi-Scale EEG Analysis

Computational Biology and Bioinformatics Third Award

This study explores the effectiveness of Convolutional Bidirectional Long Short-Term Memory (Conv-Bi-LSTM) in detecting neonatal seizure activity using Electroencephalogram (EEG) data, based…

Decoding a Variety of Concepts Including Abstract and Non-Existent Objects From Brain Activity During Mental Imagery

Computational Biology and Bioinformatics

Mental imagery is a sophisticated brain function that enables high-level inference and creation. The ability for mental imagery varies among individuals along various dimensions, such as viv…

Decoding Diabetes: Harnessing AI to Accurately Predict Real-Time and Future Blood Glucose Levels for Diabetes Management Using Diet, Exercise, Insulin Intake, and Heart Rate Variability

Computational Biology and Bioinformatics

Continuous glucose monitoring (CGM) systems are crucial in diabetes care, but focus only on monitoring blood glucose levels (BGL), neglecting diet, exercise, and medication and lacking predi…

Decoding Molecular Shifts in Late-Stage ALD: Opposing Gene Expression and Metabolic Trends Revealed Through RNA-Seq Analysis

Computational Biology and Bioinformatics

Purpose: Alcohol-related liver disease (ALD) is a leading cause of liver failure worldwide. This study aims to identify differentially expressed genes and affected biological pathways in lat…

De novo Structure-Based Design of TEM-171 Beta-Lactamase Protein Inhibitors Using Integrated Deep Learning and Multi-Scale Simulations to Combat Bacterial Resistance

Computational Biology and Bioinformatics

The emergence of TEM-171 Beta-lactamase represents a significant threat to modern antimicrobial therapy due to its ability to hydrolyze an extended spectrum of Beta-lactam antibiotics. While…

Designing Enhanced DNAJB6 Variants: A New Approach to Prevent Alzheimer's Disease by Inhibiting Amyloid-beta 42 Clumping

Computational Biology and Bioinformatics

With 50 million people suffering globally, Alzheimer’s Disease stands as one of the most devastating neurodegenerative disorders, yet no cure or preventative therapy exists (Yang et al., 202…

Designing Ligand Functionalized Synthetic Exosomes for Targeted CRISPR-Cas9 Delivery: A Multistep Computational Approach to Cancer Treatment

Computational Biology and Bioinformatics

CRISPR Cas9 is a gene-editing tool that holds immense importance for precision medicine, yet off-target effects remain as a major challenge. This project aims to design ligand-functionalized…

Development of a Novel Multi-Omics Enhanced Quantitative Structure-Activity Relationship (ME-QSAR) Model for Pancreatic Ductal Adenocarcinoma Inhibitor Discovery

Computational Biology and Bioinformatics

Traditional drug discovery exceeds 10 years and $2 billion per drug. Conventional Quantitative Structure-Activity Relationship (QSAR) models only identify single-target inhibitors and lack b…

Dopavision: A Novel Supervised Machine Learning Model for Predicting Post-Cocaine Phasic Mesolimbic Dopamine Activity in Male C57BL/6J Mice

Computational Biology and Bioinformatics

Dysregulated dopamine in the mesolimbic system is linked to disorders like schizophrenia, depression, and addiction. Low phasic dopamine release correlates with reduced drug reward sensitivi…

Early Detection of Critical Salmonellosis Cases for Pre-Emptive Treatment via Novel Biomarkers Discovered Through Protein Domain Analysis and Machine Learning

Computational Biology and Bioinformatics Fourth Award

Salmonella is a common pathogen, infecting more than a hundred million people yearly. About 8% of these cases worldwide result in life-threatening conditions around 4-7 days after exposure.…

Effectiveness of Heterogeneous COVID-19 Policies: County-Level Analyses Using Mathematical Epidemiology Models

Computational Biology and Bioinformatics

Non-pharmaceutical interventions to COVID-19 included mask mandates, social distancing mandates (banning large gatherings, advising individuals not to socialize outside their households), sc…

Epigenetic Analysis for Diabetes Risk and Resiliency

Computational Biology and Bioinformatics

Diabetes mellitus is one of the various types of major metabolic diseases that affect over 800 million people worldwide, according to the World Health Organization. The number of people livi…

Exploring the Use of Polyprenylated Benzophenones in Enhancing Efficacy of BETA-Lactam Antibiotics Through Molecular Docking in AutoDock Vina

Computational Biology and Bioinformatics

This study investigated the inhibitory potential of 41 polyprenylated benzophenones (PPBs) from Garcinia species against TEM52 ß-lactamase, aiming to identify a potential non-competitive inh…

Ferromilab: Quantum Molecular Dynamics-Derived Biclonal Antibodies Modulating Hepcidin-Ferroportin Interfaces to Mitigate Iron Dysregulation and Ferroptosis in Alzheimer's Disease

Computational Biology and Bioinformatics Third Award

Alzheimer’s Disease (AD), a neurodegenerative disorder linked to pathologies characterized with neural cognitive decline, has recently been connected to iron dysregulation and ferroptosis in…

Identification of Mutations in MicroRNA Binding Sites Within Risk Genes Associated With Diseases Through a Computational Approach

Computational Biology and Bioinformatics

MicroRNAs (miRNAs) are non-coding RNAs that bind to the coding sequences of target messenger RNAs (mRNAs), where they regulate gene expression. Mutations of miRNA binding sites within risk g…

Inference of Cell-Cell Communication to Understand the Molecular Mechanisms of Alzheimer's Disease

Computational Biology and Bioinformatics

Alzheimer’s disease (AD) is the seventh leading cause of death in the U.S. and remains incurable. Most existing therapeutics target beta-amyloid plaques, but plaque removal has shown no evid…

In silico Investigation of Biophysical Relationships Between a Unique Codon Reassignment and Morphological Plasticity in Candida Fungal Pathogens of the CTG Clade

Computational Biology and Bioinformatics Fourth Award

Pathogenic fungi of the Candida genus, including C. albicans, pose an increasing threat to global health. Almost all Candida species belong to the CTG clade, which deviates from the common g…

KAN-Fusion: Interpretable Multimodal Networks for Novel Neurodegenerative Disease Target Discovery

Computational Biology and Bioinformatics

Neurodegenerative disease therapeutic development faces hurdles from multi-omic complexity and the poor interpretability of standard ML models (e.g., MLPs), limiting target discovery. We dev…

Leveraging a Context-Aware Graph Neural Network for Drug Target Discovery in Alzheimer's Disease

Computational Biology and Bioinformatics

Alzheimer's disease (AD) is a complex, progressive neurodegenerative disorder characterized by extracellular Aß plaques, neurofibrillary tau tangles, and neuronal degeneration, involving mul…

Lung Cancer Diagnosis Using Exhaled VOC Data and Machine Learning

Computational Biology and Bioinformatics

Lung cancer is the most commonly diagnosed cancer worldwide and the leading cause of cancer-related deaths. It is difficult to diagnose accurately, especially at an early stage. No tradition…

Machine learning optimized in silico design of a de novo RAGE inhibitor: a small molecule approach to slowing the progression of inflammatory disease

Computational Biology and Bioinformatics

Inflammatory diseases affect billions of patients worldwide. Receptor for Advanced Glycation End products (RAGE) has been identified as a promising target for many inflammatory diseases, inc…

MAPS: Mangrove Analytics and Prediction System

Computational Biology and Bioinformatics

Mangroves play a crucial role in coastal protection, biodiversity support, carbon sequestration, and water purification. However, between 1996 and 2020, the Philippines lost 7,934 hectares o…

Modeling Bird Flu Mutation Patterns and Cross-Species Transmission Using Sequence Analysis and a Novel Contrastive Learning and Influence-tree Graph Attention Network (CLIGAT)

Computational Biology and Bioinformatics Second Award

Avian influenza (Bird Flu) is a highly transmissive pathogen affecting over 166 million poultry and posing significant health risks to humans. Despite progress on surface proteins, differenc…

Molecular Image-Based Explainable AI Framework Identifies Novel Candidate Antibiotics

Computational Biology and Bioinformatics (inferred)

The continued growth of antibiotic resistance and the slowing of antibiotic discovery poses a large challenge in modern medicine. Recent advances in Artificial intelligence (AI) technologies…

MRI SmarT: A Novel Multi-Modal Approach to Tumor Detection and Surgical Planning,

Computational Systems: Medical Honorable_mention Award

Multivariate Predictive Analysis of Non-Alcoholic Steatohepatitis Risk Using Comorbid Diagnoses and FibroScan Metrics

Computational Biology and Bioinformatics

Non-alcoholic steatohepatitis is a progressive liver disease that is frequently underdiagnosed due to its asymptomatic nature in earlier stages. It is strongly associated with the presence o…