Alper Bulbul | Bioinformatics | Research Excellence Award

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

 

Ulka Shirole | Biomedical signal processing | Best Researcher Award

Dr. Ulka Shirole | Biomedical signal processing | Best Researcher Award

Faculty A. C. Patil College of Engineering India

👩‍🏫 Dr. Ulka Mahesh Shirole is an esteemed academic professional currently serving as the Assistant Professor and Head of the CSE (IoT and CSBC) Department. With a robust background in electronics engineering, she has dedicated over 17 years to teaching and research. Dr. Shirole specializes in cardiac health assessment using HRV analysis and has a commendable track record in academic leadership and research publications.

Profile

Google Scholar

Education

🎓 Dr. Shirole earned her Ph.D. in Cardiac Health Assessment using HRV Analysis from NMIMS University Mumbai (2017-2022). She holds an M.E. in Electronics and Telecommunication from Mumbai University (2007-2009) and a B.E. from Bangalore University (1995-1999).

Experience

💼 Dr. Shirole has extensive teaching experience, starting as a Lecturer in the Computer Engineering Department and advancing to her current role as Assistant Professor and Head of the CSE Department. She has also served in the Electronics & Telecommunication and Electronics Engineering Departments, where she has been pivotal in course development and academic administration.

Research Interests

🔬 Her research interests include cardiac health assessment, IoT applications, blockchain technology, and data science. She has significantly contributed to the fields of electronics and telecommunication through her innovative research and publications.

Awards

🏆 Dr. Shirole has been recognized for her innovative research with the prestigious International Research Awards – Rula Award for Innovative Researcher of the Year 2020. She has also received a grant from the University of Mumbai for her academic contributions.

Publications Top Notes

📚 Dr. Shirole has authored numerous research papers and articles. Notable publications include:

“Product identification system using blockchain technology,” ACPCE Techlight, 2023 (under review).

“A mathematical model for prediction of left ventricle ejection fraction from lf/hf,” Medicine in Novel Technology and Devices, 2022 (under review).

“Covid-19 social distance monitoring via CCTV,” (2022).

“A mathematical model for prediction of LVEF from ECG in a three-point deterioration study of cardiac health in diabetics,” Technology, 2020.

“Cardiac, diabetic and normal subjects classification using decision tree and result confirmation through orthostatic stress index,” Informatics in Medicine Unlocked, 2019.