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.
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
Ohno-miRNAs: miRNA Pairs Derived From Whole-genome Duplication
Two rounds of wholegenome duplication WGD occurred about million years ago and played a major role in the evolution of the vertebrate genomes Human genes derived from WGD are called ohnologs
Immunophenotypic Changes in the Tumor and Tumor Microenvironment During Progression to Multiple Myeloma
Investigation of the cellular and molecular mechanisms of disease progression from precursor plasma cell disorders to active disease increases our understanding of multiple myeloma MM pathogenesis
Linking Spatial Drug Heterogeneity to Microbial Growth Dynamics in Theory and Experiment
Drugs play a central role in limiting bacterial population spread yet laboratory studies typically assume wellmixed environments when assessing microbial drug responses In contrast bacteria in the human body
Coupled Pharmacokinetic Model Unveils Drug-drug Interactions in Plasma Concentration
In oral drug pharmacokinetics PK drugdrug interactions are inevitable yet traditional compartmental models struggle to effectively quantify such processes This study proposes a linearly coupled twocompartment
An Interpretable Machine Learning Framework for Adverse Drug Reaction Prediction from Drug-target Interactions
Adverse drug reactions ADRs present challenges to patient safety and healthcare systems Current pharmacovigilance methods such as the Yellow Card Scheme YCS provide valuable postmarketing
GAN-enhanced Machine Learning and Metabolic Modeling Identify Reprogramming in Pancreatic Cancer
Pancreatic ductal adenocarcinoma is one of the deadliest forms of cancer presenting significant clinical challenges due to poor prognosis and limited treatment options Understanding
