Biology subjects

More, P.

Publications and source records attributed to More, P..

4 recordsLinked to original sources

bioRxiv2026

GenesetDiseaseDrugNetwork (GDDN): a web server for disease enrichment and drug prioritization

SummaryOmics technologies profile thousands of genetic and molecular features to provide a comprehensive and quantitative measure of the cellular state. Transcriptomics and proteomics have, especially, guided discoveries of the most important biomarkers and therapeutic targets. By virtue of ongoing developments in single-cell and spatial technologies, fields of targeted therapeutics and personalized medicine are rapidly advancing. However, downstream functional analysis and disease association still remain daunting tasks in bioinformatics. We address these challenges with the GenesetDiseaseDrugNetwork (GDDN) web server. GDDN facilitates functional discovery by connecting gene-sets to enriched diseases and their corresponding therapeutics in a single step. Using a ranking system that incorporates regulatory impact, specificity, and potency, GDDN effectively prioritizes drugs with the highest clinical relevance. Our platform facilitates the interpretation of omics outputs into disease associations and personalized drug identification. Availability and ImplementationThe GDDN web server is implemented in R Shiny and is freely accessible at https://cbdm-01.zdv.uni-mainz.de/shiny/piyusmor/GDDN/, supporting all major web browsers. Contactpiyusmor@uni-mainz.de Supplementary informationSupplementary data is available at Bioinformatics online.

bioinformatics↗

bioRxiv2025

Target-site Dynamics and Alternative Polyadenylation Explain Large Share of Apparent MicroRNA Differential Expression

MicroRNA (miRNA) abundance reflects a dynamic balance between biogenesis, target engagement, and decay, yet differential expression analyses typically ignore changes in target-site availability driven by alternative polyadenylation (APA). We introduce MIRNAPEX, an expression-stratification-based machine learning framework that quantifies miRNA regulatory effect sizes from RNA-seq data by integrating target-gene expression with 3'UTR isoform usage to infer effective binding-site dosage. Using pan-cancer training sets, we train models that learn relationships between transcriptomic features and miRNA log-fold changes, with APA patterns providing predictive information beyond gene expression alone. When applied to knockdowns of core APA regulators, MIRNAPEX captured widespread 3'UTR shortening and accurately anticipated miRNA-specific shifts whose direction and magnitude mirrored APA-driven changes in binding-site availability. Analysis of target-directed miRNA degradation interactions further showed that loss of distal decay-trigger sites coincides with increased miRNA abundance, consistent with reduced degradation. Together, these findings demonstrate that apparent miRNA differential expression can arise from dynamic target-site landscapes rather than altered miRNA transcription, and that neglecting this dimension can lead to misestimation of regulatory effect sizes.

bioinformatics↗

bioRxiv2025

Understudied and underprotected: biodiversity and conservation challenges in the Konkan region of Maharashtra

In biodiversity hotspots, such as the Western Ghats, periodic synthesis of existing ecological research can help identify knowledge gaps and address critical threats to biodiversity. The Maharashtra part of the Konkan region, situated between the Sahyadri foothills and the west coast, with diverse tropical vegetation, harbours unique open ecosystems, such as lateritic plateaus, and supports a multitude of threatened species, including hornbills and tigers. However, the region remains relatively understudied and has not received adequate protection through state or national conservation policies and laws. The area is undergoing rapid human-driven land-use change. These activities can impact the regions biodiversity, necessitating an effort to identify knowledge gaps and critical threats. Through a combination of a literature review and focus group discussions with 44 participants from various institutions and non-governmental organisations, we synthesised existing published information on the Konkan region of Maharashtra and identified key research gaps and conservation challenges. Our review of 138 studies found that while agroforestry and human-wildlife interactions have received some research attention, the effects of climate change on the regions biodiversity remain poorly understood. Focus group discussions highlighted major threats, including land-use changes due to expanding monoculture plantations, clear-felling of forests, forest fires, environmental pollution, and rapid infrastructure development, which are leading to habitat loss and fragmentation. Some of these concerns were validated by publicly available regional data, which revealed a 30% increase in roads, a 14% expansion of cashew plantations, and associated forest loss. This synthesis offers valuable insights for government and non-governmental organisations to inform future research and conservation efforts in the region.

ecology↗

bioRxiv2018

TAF-ChIP: An ultra-low input approach for genome wide chromatin immunoprecipitation assay

Chromatin immunoprecipitation (ChIP) followed by next generation sequencing (ChIP-Seq) is powerful technique to study transcriptional regulation. However, the requirement of millions of cells to generate results with high signal-to-noise ratio precludes it in the study of small cell populations. Here, we present a Tagmentation-Assisted Fragmentation ChIP (TAF-ChIP) and sequencing method to generate high-quality results from low cell numbers. The data obtained from the TAF-ChIP approach is amenable to standard tools for ChIP-Seq analysis, owing to its high signal-to-noise ratio. The epigenetic profiles from TAF-ChIP approach showed high agreement with conventional ChIP-Seq datasets, thereby underlining the utility of this approach.

genomics↗