A5069044989- Bioinformatics and Genomic Networks
- Antibiotic Resistance in Bacteria
- Cancer-related molecular mechanisms research
- Rheumatoid Arthritis Research and Therapies
- Gene expression and cancer classification
- Genetic Associations and Epidemiology
- Lymphoma Diagnosis and Treatment
- Evolution and Genetic Dynamics
- CRISPR and Genetic Engineering
- Bacteriophages and microbial interactions
- Cancer Mechanisms and Therapy
- Ferroptosis and cancer prognosis
- Cancer-related gene regulation
- Diabetes and associated disorders
- Ovarian cancer diagnosis and treatment
- Pharmaceutical and Antibiotic Environmental Impacts
- Peptidase Inhibition and Analysis
- Chronic Lymphocytic Leukemia Research
- vaccines and immunoinformatics approaches
- Tryptophan and brain disorders
University Hospital Bonn
2024-2025
University of Bonn
2024-2025
Adana Science and Technology University
2021-2022
University of Birmingham
2021
Schizophrenia (SCZ) is a psychiatric disorder characterized by both positive symptoms (i.e., psychosis) and negative (such as apathy, anhedonia, poverty of speech). Epidemiological data show high likelihood early onset type 2 diabetes mellitus (T2DM) in SCZ patients. However, the molecular processes that could explain epidemiological association between T2DM have not yet been characterized. Therefore, present study, we aimed to identify underlying common pathogenetic pathways T2DM. To this...
Ovarian cancer is a major cause of deaths among women. Early diagnosis and precision/personalized medicine are essential to reduce mortality morbidity ovarian cancer, as with new molecular targets accelerate drug discovery. We report here an integrated systems biology machine learning (ML) approach based on the differential coexpression analysis identify candidate biomarkers (i.e., gene modules) for serous cancer. Accordingly, four independent transcriptome datasets were statistically...
Rheumatoid arthritis (RA) is an autoimmune disease that results in the destruction of tissue by attacks on patient his or her own immune system. Current treatment strategies are not sufficient to overcome RA. In present study, various transcriptomic data from synovial fluids, fluid-derived macrophages, and blood samples patients with RA were analysed using bioinformatics approaches identify tissue-specific repurposing drug candidates for Differentially expressed genes (DEGs) identified...
Predicting bacterial growth from genome sequences is important for a rapid characterization of strains in clinical diagnostics and to disclose candidate novel targets anti-infective drugs. Previous studies have dissected the relationship between genotype mutant libraries laboratory strains, yet no study so far has examined predictive power sequence natural strains.
Gastric cancer (GC) is a prevalent disease worldwide with high mortality and poor treatment success. Early diagnosis of GC forecasting its prognosis the use biomarkers are directly relevant to achieve both personalized/precision medicine innovation in therapeutics. Gene expression signatures offer one promising avenues research this regard, as well guiding drug repurposing analyses cancers. Using publicly accessible gene datasets from Expression Omnibus The Cancer Genome Atlas (TCGA), we...
ABSTRACT Buffering between genes is fundamental for robust cellular functions. While experimentally testing all possible gene pairs infeasible, buffering can be predicted genome-wide under the assumption that a gene’s capacity depends on its expression level and absence of this primes severe fitness phenotype buffered gene. We developed BaCoN ( Ba lanced Co rrelation N etwork), post-hoc unsupervised correction method amplifies specific signals in expression-vs-fitness effect...
Abstract Escherichia coli is an important cause of bacterial infections worldwide, with multidrug resistant strains incurring substantial costs on human lives. Besides therapeutic concentrations antimicrobials in healthcare settings, the presence sub-inhibitory antimicrobial residues environment and clinics selects for resistance (AMR), but underlying genetic repertoire less well understood. We used machine-learning to predict population doubling time growth yield 1,432 genetically diverse...