Yuval Itan, Mount Sinai

Yuval Itan is a computational biology PI in the field of human genetics and genomics. His research focus is the development and application of in silico tools to facilitate the discovery of disease-causing mutations and genes in high-throughput genomic and transcriptomic data at the individual, cohort, and population levels. His main subject of interest throughout his academic career has been interdisciplinary studies of human genotype phenotype relationships at various scales, which he pursues by combining his biology and computer science skills. Biological data are accumulating exponentially, making it crucial for cutting-edge computer science disciplines to provide a solid framework for experimental biologists to best decipher large-scale human genetic problems. During his B.Sc. in computational biology (BIU, Israel), he studied experimental biology and computer science, and the dual linkage between the fields. During his master’s degree studies (UCL, UK) at the CoMPLEX (Centre for Mathematics and Physics in the Life Sciences and Experimental Biology) program of Modelling Biological Complexity he was further exposed to various interdisciplinary studies and methodologies in biology, and he chose to focus on human genetics. He continued his Ph.D. studies in the CoMPLEX program, where, under the supervision of Prof. Mark G. Thomas, he investigated two major subjects in human population and evolutionary genetics: (1) investigating, modeling, and simulating the origins and evolution of human lactase persistence genetics, and (2) identifying human-specific gene duplication events, their dates and their function, comparing the human and chimpanzee reference genomes. His next project was under the supervision of Dr. Neil Bradman where I simulated the genetic differentiation between two human populations derived from one ancestral population. He then joined Prof. Jean-Laurent Casanova’s Laboratory of Human Genetics of Infectious Diseases at The Rockefeller University as a postdoc. He was interested in computationally resolving the “needle in a haystack” problem of identifying disease-causing genes and mutations in next generation sequencing data of patients suffering from genetic disorders. He developed new tools whenever the available ones were insufficient. He has first developed an approach called “the human gene connectome” (HGC), where using a shortest distance algorithm (as in GPS navigation systems), he identified the set of biologically plausible distances, routes, and degrees of separation between all pairs of human genes, applied for prioritizing disease-causing gene variants in high throughput data. He then developed the gene damage index (GDI), where he estimated the accumulated mutational damage for protein coding human genes. Finally, he developed the mutation significance cutoff (MSC) where he calculated for each human gene a benign/damaging threshold of significance to indicate the impact of a variant in the context of the gene in which it is harbored. The main research topics of his laboratory at the Institute for Personalized Medicine at Icahn School of Medicine at Mount Sinai are identifying disease-causing mutations, genes and pathways by case-control analyses in next generation sequencing (NGS) and genotype array data of patients, and developing new methods for detecting the functional consequences of human genetic variants, in particular: (1) identifying population-specific disease causing mutations, genes and pathways in next generation sequencing data; (2) classifying gain-of-function and loss-of-function mutations using genomic, transcriptomic and proteomic data; and (3) disease-aware classification of pathogenic mutations by machine learning and deep neural network approaches. He is currently mentoring 11 individuals: two postdocs, one PhD student, two MS students, one data analyst, two trainees and three high school students. He has previously mentored two postdocs, one MD-PhD student, two PhD students, three bioinformaticians, three high school students, and five trainees. PhD committee member of three students.

Altuna Akalin, Berlin Institute for Medical Systems Biology (BIMSB), Max Delbrück Center for Molecular Medicine

Altuna Akalin is an accomplished researcher in the field of bioinformatics and data science., currently serving as the Head of the Bioinformatics and Omics Data Science Platform at the Berlin Institute of Medical Systems Biology, Max Delbrück Center. Dr. Akalin's scientific contributions are particularly noted in the analysis of sequencing data, including the development and maintenance of one of the most widely used bisulfite sequencing analysis packages, as well as a genomic data visualization toolkit. His work has culminated in a published book on genomic data analysis with CRC, showcasing his commitment to advancing the field.

In recent years, Dr. Akalin has focused on integrating deep learning into genomics and single-cell analysis, along with innovative applications in drug target identification. He has been at the forefront of using large language models for text and omics data integration, leading to the creation of platforms such as Onconaut.ai for targeted cancer therapies and 2ndOpin.io for disease diagnostics. These cutting-edge tools are currently being validated by medical professionals and are continuously evolving to support healthcare decision-making.

Driven by a long-term vision to optimize the application of data science in both academic and clinical settings, Dr. Akalin's current research emphasizes developing decision support systems for diagnostics and biomarker discovery using patient molecular signatures. His team is pioneering the use of semi-autonomous AI agents to streamline data analysis, enhancing the speed and efficiency of deriving actionable insights in healthcare.

Asif M. Khan, University of Doha for Science and Technology (UDST)

Mohammad Asif KHAN is a Professor and Associate Dean at the College of Computing and IT, University of Doha for Science and Technology, Qatar. He earned his PhD from the National University of Singapore before joining Johns Hopkins University (JHU), USA, as a faculty member. He later became part of a pioneering JHU team to establish a collaboration with Perdana University (PU) in Malaysia, where he served as the Founding Dean of the School of Data Sciences and Founding Director of the Centre for Bioinformatics. Dr. Khan was also a visiting Professor at Bezmialem Vakif University, Istanbul, through Turkey’s “International Fellowship for Outstanding Researchers.” He is currently the President of the Asia-Pacific Bioinformatics Network (APBioNET) and the Chairperson of the Executive Board of the Global Organisation for Bioinformatics Learning, Education, and Training (GOBLET). His research focuses on biological data warehousing and bioinformatics applications in virus study, immune responses, vaccines, drug design, and disease biomarkers.

Seref Gül, Bezmialem University

Dr. Şeref Gül received his bachelor's degree in Chemistry from Boğaziçi University in 2008. He completed his master's degrees in the field of computational biophysics at both Boğaziçi University and Michigan State University in 2013. He obtained his PhD in 2019 from Koç University's Department of Chemical and Biological Engineering. He continued his work at the same university as a postdoctoral researcher. From 2021 to 2023, he served as an Assistant Professor in the Department of Biotechnology at Istanbul University’s Department of Biology. Since May 2023, he has been continuing his research with his team at Bezmialem Vakıf University's Life Sciences and Biotechnology Institute, working on TÜBİTAK and TÜSEB-supported projects. His research focuses on understanding the circadian clock mechanism in mammals and discovering innovative drug candidate molecules against diseases related to the circadian clock. To date, he has published numerous works in national and international journals and books, and holds international patents. He also serves as a reviewer for national and international scientific journals.

In 2023, he was awarded the Outstanding Young Scientist Award (GEBİP) by the Turkish Academy of Sciences (TÜBA) in the field of molecular biology. In the same year, he received the Sedat Simavi Science Award.

Günseli Bayram Akçapınar, Acıbadem University

Prof. Günseli Bayram Akçapınar is a distinguished scientist specializing at the crossroads of protein engineering, computational biology, and biotechnology. She holds an M.Sc. and Ph.D. in Biological Sciences and Bioengineering from Sabancı University, and a B.Sc. in Molecular Biology and Genetics from Boğaziçi University.

During her postdoctoral research at the Vienna University of Technology (TU Wien) in Austria, Prof. Bayram Akçapınar focused on hydrophobin research. She investigated the molecular diversity, structure-function, and applications of hydrophobins—small, surface-active proteins produced by fungi. Her work contributed to understanding hydrophobin function and how hydrophobins can be engineered and utilized in industrial applications, such as enzyme immobilization.

Currently, Prof. Bayram Akçapınar holds the position of Principal Investigator in the Department of Medical Biotechnology at the Institute of Health Sciences of the Acıbadem University in Istanbul, Turkey where she also serves as the Director. In 2024, she joined the Editorial Board of Fungal Biology Reviews.

Her research is highly interdisciplinary, bridging biotechnology with bioinformatics and computational biology. Prof. Akçapınar applies computational methods to redesign proteins, enhancing their stability and functionality for industrial and medical applications. She focuses on gaining a mechanistic understanding of the protein structure-function paradigm through molecular simulations.

Kaya Bilguvar, Acıbadem University

Dr. Kaya Bilguvar holds a Ph.D. in Medical Biology and Genetics from Marmara University, obtained in 2022, and completed a postdoctoral fellowship at Yale University in 2007, following his M.D. from Marmara University in 2000. His primary research interests encompass neuroendocrine regulation, metabolic disorders such as obesity and diabetes, and the impact of metabolic signals on higher brain functions and neurodegeneration. Combining classical neurobiological techniques with endocrine and genetic methods, Dr. Bilguvar aims to comprehensively understand biological events at the organismal level and translate basic biomedical research into personalized prevention and precision therapies. Currently, Dr. Bilguvar is a professor at Acıbadem University School of Medicine in the Medical Genetics department, where he specializes in identifying the genetic bases of human diseases that affect the structure and function of the nervous system. His research employs multi-omic approaches and patient-derived 2D and 3D induced neuronal systems, with a particular focus on cerebral cortical malformations, schizophrenia, early-onset neurodegenerative syndromes, and migraine. Additionally, Dr. Bilguvar is dedicated to developing high-throughput omics methods for the early detection and profiling of brain tumors.

Gülşah Merve Kılınç, Hacettepe University

Dr. Gülşah Merve Kılınç is an assistant professor at the Department of Bioinformatics at Hacettepe University. She graduated from the Department of Biology at Hacettepe University in 2010. Upon receiving her PhD at the Department of Molecular Biology and Genetics at Bilkent University under a full merit scholarship in 2014, she joined Prof. Mehmet Somel’s research group to study ancient DNA. She continued her postdoctoral research in Stockholm, Sweden, in 1000 Ancient Genomes Project in Prof. Anders Götherström’s lab. For over the last ten years, her research is focused on ancient genomic investigation of past human populations from distinct parts of the world expanding from Anatolia to Siberia, from Eurasian Steppes to Scandinavia. She uses bioinformatics approaches to answer population genetics questions on palaeogenomics data. Her research is supported by various national and international grants and published in prestigeous journals including Cell, Science Advances, and Current Biology. Recently, she has been awarded by UNESCO-L’oreal Women in Science program 2024 for her research.

Mehmet Baysan, Istanbul Technical University

After obtaining his B.S. in Computer Science from Bilkent University in 2003, Dr. Baysan completed his M.S. and Ph.D. in Computer Science at The University of Texas at Dallas in 2005 and 2008, respectively. In 2010, Dr. Baysan switched his research focus to the area of computational biology as a post-doctoral fellow at the Neuro-Oncology Branch of the National Cancer Institute (NCI) of the NIH, USA. After his fellowship, he moved to NYU Cancer Institute and later to Weill Cornell Medical College as an Associate Research Scientist in 2013 and 2015, respectively. Currently, he is a faculty member in the Computer Engineering Department of Istanbul Technical University. Since 2010, his research has centered on improving our understanding of disease genomics using computational tools. His group's recent studies focused on efficient implementations and detailed evaluations of sequencing analysis algorithms for better utilization of sequencing technologies in both research projects and clinical practice.

Melike Dönertaş, Leibniz Institute

Dr. Melike Dönertaş is a group leader at the Leibniz Institute on Aging – Fritz Lipmann Institute (FLI) in Jena, Germany, where she leads the AI in Microbiome and Aging Research Group funded by the Carl Zeiss Foundation since 2023. Her studies started at the Middle East Technical University in Molecular Biology and Genetics, advancing to a PhD at the University of Cambridge and European Bioinformatics Institute with an EMBL fellowship. Her PhD explored computational studies on ageing and age-related diseases, focusing on genetics and drug repurposing. Dr. Dönertaş has been an active contributor to the global computational biology community through her involvement with the International Society for Computational Biology (ISCB). She chaired regional student groups across Europe, led the ISCB global student council, and now chairs the junior PIs, fostering collaboration and mentorship in the field. Her postdoctoral research at the Max Planck Institute for Biology of Aging focused on the role of microbiome in ageing, supported by the Collaborative Research Center on Predictability in Evolution (CRC1310). Later, having been awarded EMBO and MSCA postdoctoral fellowships, Dr. Dönertaş moved to the Leibniz Institute on Aging (FLI) in Jena to further integrate information theory, network biology, and machine learning to elucidate age-related changes in the microbiome. She continues at the same institute as a group leader, where they focus on computational biology and AI applications in understanding microbiome and aging dynamics, using omic datasets to quantify and intervene in functional decline during ageing.

Ruçhan Karaman, Genomize

Dr. Ruçhan Karaman earned his undergraduate degrees in Molecular Biology and Genetics as well as Chemistry from Boğaziçi University, where he also completed his master’s degree in Molecular Biology and Genetics. He pursued his PhD in Biomedical Sciences at KU Leuven, Belgium, conducting research at the VIB-Center for Cancer Biology with a focus on CRISPR-based target identification on liver cancers. During his career, Dr. Karaman has worked at prestigious institutions, including Harvard University and UT Southwestern Medical School, contributing to innovative studies in gene therapy and cancer biology.

Currently, Dr. Karaman serves as the Director of Growth Strategy at Genomize, where he leads the company’s global expansion efforts, particularly in the MENA and ASEAN regions.

Ali Çakmak, Istanbul Technical University

Ali Cakmak received his B.Sc. degree in 2003 from the Computer Engineering Department at Bilkent University, and his Ph.D. degree in 2008 from the Electrical Engineering and Computer Science Department at Case Western Reserve University. After completing his Ph.D., he worked as a post-doctoral research associate for a year in the same department. Then, he moved to the Silicon Valley, and worked as an R&D engineer as part of the Query Optimization Group at Oracle, Inc. In Fall 2020, he joined Istanbul Technical University as a faculty member in the Department of Computer Engineering. Before joining ITU, he was a faculty member at Istanbul Sehir University in the Department of Computer Science. His research interests include bioinformatics, data mining, data management, databases, query optimization, and data science.

Session 1 - Human Genetics

Moderetors: Onur Emre Onat & Asif M. Khan

Session 2 - Artificial Inteligence for Health Informatics

Moderetors: Günseli Bayram Akçapınar & Tunca Doğan

Session 3 - Multiomics Approaches

Moderators: Gülşah Merve Kılınç & Arda Çetinkaya

Session 4 - Drug Design and Development

Moderators: A.Matteen Rafiqi & Şükrü Anıl Doğan

Session 5 - Genome Research

Moderators: Yeşim Aydın Son & İdil Yet

Session 6 - Protein Structure & Function

Moderators: Şeref Gül & Özge Şensoy

Session 7 - Machine Learning Applications

Moderators: Mehmet Baysan & Arzu Karahan

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