Areejit Samal

This paper introduces AgingHallmarksDB, a resource for systems-level analysis of aging hallmarks and associated genes, demonstrating its utility through various analyses of disease and transcriptome data.

NANHA is a curated database of non-invasive brain stimulation studies in neurodevelopmental disorders, providing standardized data for analysis and protocol development.

This study benchmarks AI models for predicting nuclear receptor activity using Tox21 assays, finding that tree-based models perform better on imbalanced data while deep learning shows robustness on moderate imbalances.

TickMapKB is a spatial knowledgebase compiling tick species, pathogens, and associated data in India to aid in disease surveillance and resistance management.

This study identifies SecA1 and TatA as critical for Mycobacterium tuberculosis membrane integrity through multi-omics and functional genetics analyses.

This study constructs computational adverse outcome pathways for organic mercury toxicity in fish using an integrative network-based framework and curated toxicological data.

This paper introduces ReCAnt, a resource compiling data on 690 aquaculture chemicals and their ecotoxicity, highlighting regulatory gaps and environmental fate.

This study updates the DEDuCT database with 1043 EDCs and 796 endpoints from 3269 articles, constructs a toxicology knowledge graph, and aligns it with FAIR principles for EDC research and regulation.

The paper uses persistent homology to analyze brain functional connectivity changes in healthy aging and ASD, identifying clinically relevant regions with node persistence.

This study uses network toxicology to analyze the toxic effects of inorganic arsenic and cadmium on human and ecosystem health, identifying 51 and 78 adverse outcome pathways respectively.

This paper creates a database of tattoo ink chemicals and their toxicities, identifying hazardous substances and regulatory coverage.

This study evaluates threshold majority rules in gene regulatory network modeling, finding they lack biological realism and fail to capture key dynamics observed in empirical data.

This study computationally identifies cyclotides from Viola odorata as potential inhibitors of Streptococcus pneumoniae neuraminidase, with five top candidates showing stability in molecular dynamics simulations.

sCentInDB is a manually curated database of essential oil chemical profiles from 554 Indian medicinal plants, providing metadata and chemical space analysis for research and quality standards.

This study shows that biologically meaningful Boolean functions stabilize random Boolean network dynamics more than random functions, across varying network sizes and connectivities.

UVREK compiles manually curated data on biomolecules induced by UV radiation exposure, revealing transcription-related processes and pathways involved in cancer and aging.

This study uses network-based frameworks to assess the ecotoxicological effects of petroleum hydrocarbons and their risks to aquatic ecosystems.

This study constructs a stressor-centric adverse outcome pathway network for plastic additives using toxicogenomic data, identifying 1287 additive-AOP associations and demonstrating their utility for risk assessment.

The paper evaluates how different regulatory logic rules affect the structural features of Boolean network state transition graphs, finding that biologically meaningful rules improve bushiness and convergence.

The paper analyzes Boolean functions in biological networks and finds generalized chain functions are significantly enriched in NCFs across multiple datasets.

This study constructs the first adverse outcome pathway network for inorganic cadmium toxicity by integrating data from multiple sources and analyzing key events and relationships.

ViCEKb compiles 113 unique chemical triggers of vitiligo from literature, standardizes chemical data, and highlights their biological impacts and regulatory status.

T9GPred predicts Type 9 secretion system, gliding motility, and associated secreted proteins in Bacteroidetes strains using curated experimental data and signal domain analysis.

This study applies discrete Ricci curvatures to functional connectivity networks of young and older adults, finding age-related differences in brain regions associated with cognitive domains and behavioral scores.

The paper develops a method to select Boolean gene regulatory network models by leveraging developmental landscapes and attractor stability, finding that a recent model fails to respect expected cell state hierarchies and proposing an algorithm to correct this.

EPEK compiles and analyzes gene, metabolite, and SNP expression data from human ectopic pregnancy studies to identify potential diagnostic markers and cellular signaling processes involved.

This study applies graph Ricci curvatures to compare functional connectivity networks in ASD and typically developing individuals, finding region-specific differences associated with cognitive impairments and potential therapeutic targets.

The paper investigates composition structures in bipartite Boolean network models of gene regulation, finding they are enriched in real biological networks but likely driven by nested canalyzing and read-once functions.

The paper analyzes Boolean functions in gene regulatory networks, finding that odd-biased and read-once functions are enriched due to their minimal Boolean complexity and average sensitivity.

MeFSAT is a curated database of secondary metabolites from medicinal fungi, providing chemical and therapeutic information to aid drug discovery.