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

 

Mahsa Darbandi | Molecular Biology | Best Researcher Award

Published on by Academic Achievements

Dr. Mahsa Darbandi | Molecular Biology | Best Researcher Award

Postdoctoral | Hope generation foundation | Iran

Short Biography 🌟

Mahsa Sara Darbandi is a dedicated researcher in the field of reproductive biotechnology, renowned for her expertise in oxidative stress impacts on spermatozoa and genetic, epigenetic, and metabolite status. She holds a Ph.D. from the Avicenna Research Institute, Tehran, Iran, where her doctoral research focused on understanding these complex interactions. Mahsa has furthered her knowledge through international programs like the American Center for Reproductive Medicine (ACRM), enhancing her skills in proteomic analysis and artificial intelligence applications in medicine.

Profile:

ORCID

Education 📚

Mahsa earned her Bachelor of Science in Biology from the University of Tabriz, Iran, followed by a Master of Science in Biochemistry from the University of Mashhad. Her thesis investigated the effects of electro-acupuncture combined with a low-calorie diet on body weight and plasma leptin levels in obese individuals. Subsequently, she pursued her Ph.D. in Reproductive Biotechnology at the Avicenna Research Institute, where she explored the intricate relationship between oxidative stress and sperm biology.

Experience 💼

Her professional journey includes significant milestones such as the Summer Mentorship Program and ART Training Program at ACRM, Cleveland Clinic, OH, where she honed her skills in laboratory methods and quality assurance in human reproduction. As part of the ACRM Global Researcher Program, Mahsa engaged in meta-analysis projects focusing on male infertility, demonstrating her proficiency in data analysis and scientific writing.

Research Interest 🔬

Mahsa’s research interests encompass the application of artificial intelligence and machine learning in medical image processing and big data analysis, particularly in the context of early cancer detection and personalized medicine for breast and prostate cancers. Her current endeavors at the Hope Generation Foundation in Tehran aim to advance early detection techniques in oncology.

Awards 🏆

Throughout her career, Mahsa has been recognized for her contributions to reproductive biology and male infertility research. Her work has been published in prestigious journals and cited extensively, underscoring her impact on the field.

Publications 📄

  • Publication Title: “Impact of Oxidative Stress on Sperm DNA Integrity and Its Clinical Significance in Male Infertility”
    • Journal: Journal of Reproduction & Infertility
    • Summary: This study explores the detrimental effects of oxidative stress on sperm DNA integrity and its implications for male infertility. It discusses potential clinical interventions to mitigate these effects.
  • Publication Title: “Epigenetic Modifications in Spermatozoa: Potential Implications for Assisted Reproductive Technologies”
    • Journal: Andrologia
    • Summary: This paper reviews epigenetic changes in spermatozoa and their relevance to assisted reproductive technologies (ART). It discusses how these modifications could influence embryo development and reproductive outcomes.
  • Publication Title: “Metabolomic Profiling of Spermatozoa in Men with Varicocele-Associated Infertility”
    • Journal: Systems Biology in Reproductive Medicine
    • Summary: This research employs metabolomic profiling to identify metabolic alterations in spermatozoa from men with varicocele-associated infertility, offering insights into potential biomarkers and therapeutic targets.
  • Publication Title: “Application of Artificial Intelligence in Medical Image Processing for Early Detection of Breast Cancer”
    • Journal: Journal of Medical Imaging and Health Informatics
    • Summary: This article explores the application of artificial intelligence techniques in medical image processing specifically for early detection of breast cancer, highlighting the potential for improved diagnostic accuracy and patient outcomes.
  • Publication Title: “Genetic and Epigenetic Biomarkers in Prostate Cancer: Implications for Personalized Medicine”
    • Journal: Current Genomics
    • Summary: This review examines genetic and epigenetic biomarkers associated with prostate cancer, emphasizing their potential utility in personalized medicine approaches for diagnosis, prognosis, and treatment selection.