Alper Bulbul | Bioinformatics | Research Excellence Award

Published on by Academic Achievements

Mr. Alper Bulbul | Bioinformatics | Research Excellence Award 

Mr. Alper Bulbul | Bioinformatics | PhD Candidate at Acibadem University | Turkey

Bioinformatics forms the foundation of Mr. Alper Bulbul’s professional expertise and research trajectory, shaping his work as a highly committed PhD student with a strong academic grounding in molecular biology, genetics, biostatistics, and computational sciences. Mr. Alper Bulbul completed undergraduate and graduate training in Molecular Biology and Genetics at Istanbul Technical University, further advancing into doctoral research at Acibadem University within the Department of Biostatistics and Bioinformatics. His professional experience includes co-founding a biotechnology start-up, where he contributed to the development of a biosensor designed to measure cancer-related biomarkers with high precision using aptamer-based detection and electrochemical analysis, supported through a national entrepreneurship research program. His primary research interests focus on complex genetic diseases, particularly Multiple Sclerosis, investigated through high-throughput sequencing, Genome-Wide Association Studies, network modeling, gene expression prediction, and disease prognosis interpretation. Mr. Alper Bulbul is proficient in advanced bioinformatics methodologies such as linkage analysis using MERLIN, Allegro, GeneHunter, and pVAAST, variant calling with DeepVariant, GATK, and PLINK, structural and molecular docking approaches using ZDOCK, HADDOCK, and Autodock Vina, molecular dynamics simulations on AMBER, GROMACS, and NAMD platforms, and knowledge graph-based disease gene prioritization using Exomiser and HGPEC. His computational strengths include Python programming with analytics frameworks, R-based statistical pipelines, Linux environment workflows, and Nextflow-based pipeline orchestration, along with SQL database familiarity and application of cloud-computing architectures. His research vision integrates bioinformatics with machine learning to investigate variant pathogenicity, protein behavior, and clinically relevant gene-interaction consequences. He has developed high-performance predictive models for systemic autoinflammatory conditions and conducted whole-exome sequencing studies on familial Multiple Sclerosis to identify the contribution of both rare and common variants, supported by network and enrichment analyses to uncover related biological pathways. The scholarly impact of Mr. Alper Bulbul is reflected through contributions to peer-reviewed publications, interdisciplinary collaborations in translational genetics, and growing citation metrics that illustrate continued relevance of his work. Recognitions include entrepreneurial support funding and acknowledgment for impactful research contributions at the intersection of computational genomics and disease diagnostics. In summary, Mr. Alper Bulbul seeks to advance precision medicine and genomic interpretation through integrative Bioinformatics approaches, supported by interdisciplinary expertise, strong analytical reasoning, and dedication to improving patient outcomes through data-driven translational genetics.

Profile: Google Scholar | ORCID

Featured Publications 

Szydlowski, L. M., Bulbul, A. A., Simpson, A. C., Kaya, D. E., Singh, N. K., … (2024). Adaptation to space conditions of novel bacterial species isolated from the International Space Station revealed by functional gene annotations and comparative genome analysis. Microbiome, 12(1), 190. Citations: 16
Everest, E., Ahangari, M., Uygunoglu, U., Tutuncu, M., Bulbul, A., Saip, S., … (2022). Investigating the role of common and rare variants in multiplex multiple sclerosis families reveals an increased burden of common risk variation. Scientific Reports, 12(1), 16984. Citations: 13
Inci, N., Akyildiz, E. O., Bulbul, A. A., Turanli, E. T., Akgun, E., Baykal, A. T., Colak, F., … (2022). Transcriptomics and proteomics analyses reveal JAK signaling and inflammatory phenotypes during cellular senescence in blind mole rats: the reflections of superior biology. Biology, 11(9), 1253. Citations: 9
Everest, E., Uygunoglu, U., Tutuncu, M., Bulbul, A., Onat, U. I., Unal, M., Avsar, T., … (2023). Prospective outcome analysis of multiple sclerosis cases reveals candidate prognostic cerebrospinal fluid markers. PLOS One, 18(6), e0287463. Citations: 7
Büyükgöl, F., Gürdamar, B., Aluçlu, M. U., Beckmann, Y., Bilguvar, K., Boz, C., … (2025). Exome sequencing reveals low-frequency and rare variant contributions to multiple sclerosis susceptibility in Turkish families. Scientific Reports, 15(1), 11682. Citations: 1
Kilinc, O. C., Gayibova, K., Onen, M. O., Onat, U. I., Bulbul, A., Timucin, A. C., Ugurlu, S., … (2024). A rare case of uncharacterized autoinflammatory disease: Patient carrying variations in NLRP3 and TNFRSF1A genes. American Journal of Medical Genetics Part A, 194(10), e63715. Citations: 1

 

Álvaro Torres-Martos | Bioinformatics | Best Researcher Award

Published on by Academic Achievements

Mr . Álvaro Torres-Martos | Bioinformatics | Best Researcher Award 

PhD student , University of Granada , Spain

Álvaro Torres-Martos is a dedicated Pre-Doctoral Fellow at the Center of Biomedical Research and “José Mataix Verdú” Institute of Nutrition and Food Technology (INYTA), University of Granada. His research bridges bioinformatics, biostatistics, and precision medicine, focusing on the molecular and genetic underpinnings of metabolic disorders. Álvaro combines his expertise in multi-omics and artificial intelligence to advance our understanding of obesity, insulin resistance, and non-communicable diseases.

Profile

ORCiD

Strengths for the Award

  1. Cutting-Edge Research Experience: Álvaro Torres-Martos has been involved in high-impact research projects such as the ACTIBATE project and EXOMAIR, focusing on novel therapeutic targets and precision medicine. His work on molecular translators and the exposome demonstrates a commitment to advancing the understanding of complex biological systems and diseases.
  2. Academic Background and Progression: With a solid foundation in Biochemistry and Bioinformatics, Álvaro’s transition from a Bachelor’s degree to a Master’s and then to a Pre-doctoral Researcher shows a strong academic trajectory. His current role as a faculty member at the University of Granada further highlights his growing expertise in the field.
  3. High-Quality Publications: Álvaro has published in reputable journals like Artificial Intelligence in Medicine and Translational Psychiatry, showcasing his contributions to precision nutrition, machine learning applications, and metabolic health. His work is well-cited and reflects a significant impact on his research area.
  4. Innovative Tools and Recognition: His involvement in developing the ObMetrics Shiny app and winning the III Bioinformatics Datathon indicates his ability to translate research into practical tools. These achievements underscore his innovation and practical application of his research.
  5. Broad Skill Set: Álvaro has completed various courses and certifications, including advanced data science skills and programming in R and Python. This diverse skill set supports his ability to conduct and present high-quality research.

Areas for Improvement 

  1. Broader Research Impact: While Álvaro’s research is highly specialized, expanding the scope to interdisciplinary areas or applied research in clinical settings could enhance the broader impact of his work.
  2. Increased Visibility: Although he has participated in numerous congresses, further efforts to increase the visibility of his research through collaborations, media outreach, or higher-profile conferences could amplify his contributions.
  3. Grant Acquisition: Securing larger research grants or funding from diverse sources could support more ambitious projects and collaborations, further strengthening his research portfolio.

    Education 

    Álvaro earned his Bachelor’s degree in Biochemistry from the University of Granada (UGR) in 2020. He then pursued a Master’s degree in Bioinformatics and Biostatistics at the Open University of Catalonia (UOC) from 2021 to 2022. Currently, he is a faculty member in the Department of Biochemistry and Molecular Biology II at the University of Granada, where he continues his research and academic contributions.

    Experience 

    • 2022-2023: Bioinformatic Researcher at the ACTIBATE project, University of Granada. This role focused on molecular translators of exercise and brown adipose tissue activation, searching for new therapeutic targets in intercellular communication.
    • 2023-2026: Pre-doctoral Researcher for EXOMAIR, University of Granada. This project aims to analyze the exposome and omics using artificial intelligence to study their impact on obesity, insulin resistance, and metabolic health.
    • 2024: Academic Visitor at the University of Oxford, focusing on dietary and behavioral phenotypes and non-communicable disease risk through a multi-omics approach.

    Research Interests 

    Álvaro’s research interests include the application of multi-omics and artificial intelligence in precision medicine, with a particular focus on metabolic disorders such as obesity and insulin resistance. He is also interested in the interaction between genetic risk factors and environmental influences on health outcomes.

    Awards 

    • Winner of the III Bioinformatics Datathon organized by the Bioinformatics Conference, University of Granada.
    • Developed the ObMetrics Shiny app, enhancing metabolic syndrome analysis for pediatric populations.

    Publications