The current members of the Network Pharmacology for Precision Medicine group.
Dr. Jing Tang is a tenure-track Assistant Professor in statistics at the Faculty of Medicine and Group Leader at the Institute for Molecular Medicine Finland. He received his PhD in Statistics from the University of Helsinki in 2009. He was a research scientist in Systems biology at the Technical Research Centre of Finland (VTT) in 2008-2011. Since 2012 he started at FIMM as a senior researcher focusing on computational network medicine. He received the prestigious ERC Starting Grant in 2016.
Dr. Johanna Eriksson joined the group in November of 2019 to perform the experimental validation of the pharmacology network models developed by computational methods. She received her PhD in genetics from the University of Helsinki in 2015. In her PhD and postdoctoral studies, she has focused on identifying prognostic markers and therapeutic targets for metastasized melanoma.
Research interests: gene expression profiling, biomarker discovery
Dr. Mohieddin Jafari is a senior researcher working on systems pharmacology and integrating complex biological networks to develop mechanistic biomedicine. He received his Ph.D. in Applied Proteomics from Beheshti University of Medical Science in 2013. During his scholar fellowship in Proteomics Resource at Harvard School of Public Health (HSPH) and the close collaboration with Institute for research in fundamental sciences (IPM), he has got experience in both pipetting (wet-lab methods) and programming (dry-lab methods) skills. After that, He has worked as a research scientist in computational systems biology at Pasteur Institute of Iran in 2013-2018.
Research interests: network biology, proteomics
Dr. Ziaurrehman Tanoli is working as senior researcher in the field of computational biology. He completed his PhD in machine learning from Pakistan Institute of Engineering and Applied Sciences (PIEAS) in 2013. During PhD, he also worked as visiting researcher at university of Helsinki for 1.5 years (topic: reclassification of ambiguous GPCRs). After PhD, he has worked as postdoctoral researcher at university of Sannio, Italy on project: ‘Identification of long noncoding RNAs using machine learning’. Later on, he joined Institute for Molecular Medicine Finland (FIMM) as postdoctoral researcher (2015-2018). He developed two platforms for integration and visualization of drug target interactions profiles:
Drug Target Commons (DTC: http://drugtargetcommons.fimm.fi/)
Drug Target Profiler (DTP: http://drugtargetprofiler.fimm.fi/)
Research interests: computational biology, machine learning, bioinformatics
Ziaurrehman Tanoli google scholar: https://scholar.google.fi/citations?hl=en&user=msoqalcAAAAJ
Dr. Alberto Pessia is a postdoctoral researcher working on drug combination and bioassays statistical models. He received his PhD in Statistics from the University of Helsinki in 2017 and joined the Network Pharmacology for Precision Medicine group at the beginning of 2018. During the years 2016-2017 he was the principal biostatistician/bioinformatician at the FIMM Metabolomics Unit.
Research interests: drug screen data analysis, metabolomics data analysis, computational statistics, bayesian Inference, unsupervised machine learning.
Dr. Peter Jakubik is a postdoctoral researcher working on algorithms revealing temporal and spatial heterogeneity of single cancer cells.
Research interests: clonal evolution, temporal and spatial heterogeneity of cancer cells
Dr. Ali Amiryousefi is a postdoctoral researcher focusing on the statistical integration of drug response and omics data. He is holding the MSc in Bayesian statistics and decision analysis and received his PhD in Bioinformatics from the University of Helsinki. He has also worked at the THL as a statistical consultant.
Research interests: bayesian statistics, bioinformatics, single-cell data analysis.
Alina Malyutina is a doctoral researcher whose main focus is on predicting personalized drug combinations. She is working on development of clinically-relevant computational and statistical methods for the rational design of drug combinations for individual cancer patients by leveraging the drug sensitivity and molecular data at the cell-lineage level. She received her MSc degree in Computational Engineering at the Lappeenranta University of Technology and joined FIMM as a FIMM-EMBL/HIIT PhD rotation student.
Research interests: bioinformatics, biostatistics, drug screen data analysis, systems biology
Yinyin Wang got her Bachelor degree in Nanjing University of Chinese Medicine, Science of Chinese Pharmacology in china in 2014. Then, she studied in East China University of Science and Technology, majored in Pharmaceutical Science , and got her Master degree in 2017 in china.
Research interest: network pharmacology modeling for herb medicine
Wenyu Wang is a PhD student focusing on integrative data analysis of gene essentiality to help drug discovery. He finished his undergraduate education of Medicine in Xi’an Jiaotong University in China (2015). After that, he started his research life in the same university focusing on developing and applying computational frameworks to omics dataset (i.e. GWAS dataset). After receiving his Master degree in Epidemiology and Statistics, he joined FIMM as a rotation student and worked in three different computational groups before starting his personal PhD projects in Network Pharmacology for Precision Medicine group.
Research interests: Omics data integration, system biomedicine, computational statistics and machine learning.
Bulat Zagidullin is a PhD student working on predicting the effects of drug combinations using AI-based approaches He received a BSc in Biochemical Engineering degree from the Jacobs University Bremen (JUB) in 2011. In 2017 he received his MSc in Pharmaceutical Biotechnology from the Martin Luther University Halle-Wittenberg. He is using computational statistics, machine learning and network-based methods to integrate pharmacological and molecular biology datasets.
Research interests: AI-based models for drug discovery
Joseph Saad received his BSc in Bioinformatics from the Lebanese American University (LAU) in 2016 and his MSc in Drug Discovery and Development from the University of Turku (UTU) in 2018. He is currently a doctoral student in the fields of personalized and translational medicine, at the Institute for Molecular Medicine Finland (FIMM). His research is centered around the implementation of bioinformatics methods to identify molecular biomarkers associated with response to novel drugs and drug combinations for the treatment of hematological malignancies.
Jehad got his bachelor degree in 2013 with excellent grade in Computer Engineering from Islamic University of Gaza, Palestine. After that, he has worked at Islamic University of Gaza as a (part time) Teaching assistant. Also he has worked as a coordinator for fifth International Conference on Engineering and Sustainability (ICES5). He finished his master degree in computer science from Eötvös Loránd University-Hungary. After that, he has worked as a project researcher at University of Eastern Finland. Currently, he is working as a project researcher in bioinformatics at FIMM-Helsinki.
Research interests: machine learning, meta-learning, data mining, bioinformatics.
Shuyu Zheng joined the group as a bioinformatician. She studied clinical medicine for her Bachelor degree before starting her postgraduate research in the lab. After receiving her MSc of Oncology in 2017, she has been working as a part-time research assistant, providing bioinformatics and data analysis support to clinicians with a main focus on radiation oncology.
Research interest: Radiation and chemotherapy combination therapy, clinical and high-throughput data analysis, statistical and machine learning modeling
Dalal Aldahdooh is a research assistant focusing on developing software tools to enable personalized medicine. She has got her bachelor degree from Islamic University of Gaza, Palestine. After that, she has worked as WordPress developer at Business and Technology Incubator-BTI. She has participated in different summer school programming courses.
Professor Hong-Gee Kim is a visiting professor from Seoul National University, Republic of Korea. His group is developping text mining tools for biomedical knowledge discovery.
Group website: http://bike.snu.ac.kr/