Adil Mardinoğlu

Metacontam is a decontamination method for metagenomic data that improves detection of low-abundance contaminants without needing negative controls.

G-VEP accelerates variant effect prediction in clinical whole-genome sequencing by using GPU acceleration, reducing runtime from 72 minutes to 4 minutes with no loss of accuracy.

The paper constructs tissue- and cell-type-specific metabolic models to study the effects of a high-sugar, high-fat diet on liver metabolism, revealing metabolic reprogramming and dysfunction.

The paper identifies oral-gut microbial translocation in ACLD patients linked to intestinal barrier dysfunction and hepatic fibrosis, with prtC encoding bacteria as a biomarker.

This study investigates microbiome signatures in the oral-gut-brain axis and their role in Parkinson's disease and cognitive decline.

The paper identifies two types of antimicrobial resistant bacteria in the gut microbiome after antibiotic treatment and shows how one type persists and reshapes the microbial community.

This study investigates the effects of JNK inhibition on metabolic dysfunction caused by sucrose overconsumption in rats using multi-tissue network analysis.

Standard-GEM provides a template for reproducible genome-scale metabolic model development following FAIR principles and software best practices.

The paper identifies three metabolic at-risk profiles in HIV-treated patients using multi-omics integration, highlighting dysregulated metabolism and microbiome interactions.

This study identifies immunomodulatory peptides deregulated in breast cancer using single-cell and spatial transcriptomics, and proposes drugs to modulate their expression.

This study identifies PKLR as a therapeutic target for NAFLD and validates two drug candidates through in vitro and in vivo experiments.

The paper annotates all human protein-coding genes with their function and spatial distribution across cell types using single-cell transcriptomics data and introduces a new classification tool.

GutMicroNet provides an interactive platform to explore gut microbiome interaction networks using data from the Human Gut Microbiome Atlas.

This study identifies dysregulated transcriptional regulators in NAFLD using network analysis and integrates transcriptomic data with metabolic models.

This study identifies retinoids and sex hormone dysregulation as ageing-related features in Alzheimer's and Parkinson's disease subclasses using transcriptomic and metabolic analyses.

The paper analyzes transcriptomic changes in heart and other metabolically active tissues after myocardial infarction in mice, identifying common and tissue-specific biological responses.

iNetModels 2.0 provides an interactive platform for visualizing and exploring multi-omics associations in human health and disease.

The paper investigates the prognostic significance of PKM transcripts in 25 cancers and identifies a prognostic signature in KIRC, revealing functional roles of alternatively spliced PKM transcripts.

Memote, open-source Python software, runs a community-maintained, partly scored test suite (consistency, biomass, annotations, optional experimental data) on SBML-encoded genome-scale metabolic models, once or through continuous integration.

The paper identifies two ccRCC subtypes based on PKM alternative splicing and proposes drug repurposing for each subtype.

RMetD2 integrates differentially expressed genes into genome-scale metabolic models to reveal metabolic differences between conditions, outperforming existing methods in capturing experimentally observed features.

The paper maps and characterizes the human secretome by annotating 2,623 predicted secreted proteins and their spatial distribution, using a high-throughput cell factory for recombinant protein production and analysis.