Research Insights
Research Insights section focuses on the cutting-edge and breakthrough research that is happening all over the world. Laboratories across the globe are working hard to develop drugs and therapies for various diseases and research insights directly from them add tremendous value.
Heterogeneous Biological Graph Convolutional Network for Drug-target Interaction Prediction
Drugtarget interaction prediction plays a critical role in drug discovery by identifying potential therapeutic targets and elucidating underlying molecular mechanisms Howeve
Exploring Hypoxia-related Genes as Prognostic Indicators in Lung Adenocarcinoma
Lung adenocarcinoma LUAD is a leading cause of cancerrelated mortality with hypoxia contributing to tumor progression
Mapping Metabolic Reprogramming in Lung and Breast Cancer Through Integrative Bioinformatics
Metabolic reprogramming is central to cancer biology enabling tumor cells to sustain rapid proliferation resist stress and adapt to therapy However these alterations are highly heterogeneous across cancer types
Interpretable miRNA-based Prediction Model for Early Detection of Pancreatic Cancer: Development and Cross-platform Validation
Pancreatic cancer remains one of the most lethal malignancies largely due to delayed diagnosis Although microRNA miRNA biomarkers show promise many previous studies lack crossplatform validation
Systematic Identification of Pan-cancer Single-gene Expression Biomarkers in Drug High-throughput Screens
Precision oncology relies on molecular biomarkers to stratify patients into responders and nonresponders to a given treatment Although gene expression profiles have historically been explored for biomarker discovery
Uncovering the Mechanisms of Synergistic Drug Combinations in Non-small Cell Lung Cancer Through Metagene-based Classification
Drug resistance remains a significant challenge in treating nonsmall cell lung cancer NSCLC Identifying synergistic drug combinations that simultaneously target multiple signaling pathways is crucial
Using Cell-specific Late-phase Asthma mRNA Biomarkers to Repurpose Drugs that Concurrently Reverse Disease Signatures Across Multiple Immune Cell-types
The allergeninduced latephase asthmatic response LAR is used to study the mechanisms and treatment of asthma
Gene Expression and Metadata Based Identification of Key Genes for Lung Cancer, COPD, and IPF Using Machine Learning and Statistical Models
Lung cancer LC is one of the most prevalent and deadly cancers globally presenting a major public health challenge Patients with chronic obstructive pulmonary disease COPD and idiopathic pulmonary fibrosis IPF
Enhancing Anticancer Peptide Discovery: A Fusion-centric Framework with Conditional Diffusion for Prediction and Generation
Anticancer peptides ACPs are short bioactive sequences that selectively target tumor cells with minimal toxicity positioning them as promising candidates for nextgeneration cancer therapies However existing computational
Modelling Transcription with Explainable AI Uncovers Context-specific Epigenetic Gene Regulation at Promoters and Gene Bodies
Transcriptional regulation involves complex interactions with chromatinassociated proteins but disentangling these mechanistically remains challenging Here we generate deep learning models to predict RNA PolII occupancy
