Members of the Aittokallio's research group
Tero Aittokallio received his PhD in Applied Mathematics from the University of Turku in 2001, under the supervision of Prof. Mats Gyllenberg. He then did his post-doctoral training in the Systems Biology Lab at the Institut Pasteur (2006-2007), with Dr. Benno Schwikowski, where he focused on network biology applications using high-throughput experimental assays and network analysis tools such as Cytoscape. In 2007, Dr. Aittokallio launched his independent career as a principal investigator in the Turku Biomathematics Research Group, where he received a five-year appointment as an Academy of Finland Research Fellow (2007-2012). Tero Aittokallio joined FIMM as EMBL Group Leader in the fall of 2011.
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FIMM-EMBL Doctoral Student
Yevhen Akimov received his M.Sc. in Biophysics from the Sevastopol National Technical University. In 2015, he started at Institute for Molecular Medicine Finland as a research assistant in the Sergey Kuznetsov group. Then he got enrolled in FIMM-EMBL Ph.D. program in 2016, joining the Computational Systems Medicine group under Prof. Tero Aittokallio's supervision. Akimov Yevhen's research is focused on the development of next-generation technologies and analysis algorithms for clone tracing experiments tailored to reconstruct clonal heterogeneity of cancer cells. To address this goal, Yevhen Akimov is developing a synthetic biology method for clone isolation based on clone-specific label sequence (DNA-barcode) and statistical methods for the analysis of clonal representation
Yingjia Chen received her BS in Pharmaceutics in June 2018 and graduated from Shanghai Institute of Materia Medica with a MS in Computer-Aided Drug Design. In 2021, She joined Prof. Tero Aittokallio's group at FIMM as a doctoral student. She is interested in leveraging computational tools and approaches to study cancer. Her research focuses on finding effective personalized drug combination therapy and identifying multi-omics biomarker panels for patients with leukemia.
Prson Gautam received his MSc degree in Applied Biotechnology at the Uppsala University, Sweden, and completed his PhD at the Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Finland in Jan 2018. During his PhD he used chemical systems biology approach to study triple negative breast cancer with an aim to establish precision based therapeutic strategies under the supervision of Prof. Krister Wennerberg. Currently, he is working as a senior researcher in the group. In FIMM, he aims to identify drug or drug combination against pancreatic and breast cancer, applying drug repurposing studies. Besides, he is also involved in multiple bioinformatics project to develop machine learning based predictive models to predict drug/drug combination effects and biomarkers. In addition, he is also working as global study/project manager at pharmaceutical company Bayer, where he is running/ managing first in human to phase 3 clinical trials.
Liye He received his MSc degree in computer science from University of Helsinki, Finland. He started his PhD at the Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Finland since July 2015 under the supervision of Prof. Tero Aittokallio. His PhD projects focuse on building computational tools to identify synergistic and personalised drug combinations for cancer patients using different types of data such as sequencing data. He is interested in applying machine learning methods to tackling real-world challenges.
Aleksandr Ianevski received his B.S. in software engineering in July 2015 and M.S. in Bioinformatics at the Aalto University in November 2018. Currently, Aleksandr is a doctoral student in the Computational Systems Medicine research group lead by Tero Aittokallio. He specializes in machine learning, development of computational, biologically relevant methods, statistical data analysis, big data processing, bioinformatics data analysis, bioinformatics tool (including web-tools) development, and interactive visualizations.
Anil Kumar received his Ph.D. in Life Science from the Academy of Scientific and Industrial Research 2017 at CSIR-Institute of Genomics and Integrative Biology, New Delhi, under the supervision of Prof. Dwaipayan Bharadwaj. He then joined the Computational Systems Medicine group at FIMM with Prof. Tero Aittokallio as a post-doctoral researcher. His research focuses on the development of methods for the selection of effective and personalized drug combinations for cancer patients using machine learning and molecular data (e.g. exome-sequencing, single-cell RNA sequencing). His research also focuses on identifying the pharmacogenetic variants for various drugs and drug combinations for AML. Currently, he is a joint post-doctoral fellow between Mark Daly and Tero Aittokallio group at FIMM.
Mitro Miihkinen obtained his PhD from the University of Turku in the fields of molecular cell biology and drug development in 2020. During his PhD Mitro studied cancer-relevant cell adhesion processes using both targeted and de novo approaches under the dual supervision of Johanna Ivaska and Guillaume Jacquemet. Since computational approaches are indispensable for modern life-sciences, he then joined Tero Aittokallio’s lab to achieve full competency in both experimental and computational aspects of biomedicine. In Aittokallio lab, Mitro’s main focus is to uncover illness-defining cellular traits by using powerful experimental-computational approaches with a heavy focus on advanced cancer. His reseach aims at producing new biological insights together with novel and viable treatment options to improve patient well-being.
Nora has been working as a laboratory technician in Tero Aittokallio's and Emmy Verschuren's groups since 2019. She graduated as a biomedical laboratory scientist in 2018, and before joining FIMM, she worked in the Children's and Women's hospital and Anticoagulation laboratories (HUSLAB). Nora did her Bachelor's thesis and practical training in Pirta Hotulainen's lab (Minerva) where she found the world of research. At FIMM, she has learned different techniques including cell culture, genotyping, IHC and tissue preparation, drug screening and CRISPR editing. Outside of work, she enjoys spending time with family, friends and with her active Nova Scotian Duck Tolling Retriever.
Xiangju Qin received her PhD degree in computer science from University College Dublin in 2015, under the supervision of Prof. Pádraig Cunningham. Her research interests include probabilistic and Bayesian Inference, latent variable modelling (Matrix Factorization, Mixture Models, Topic Models), Gaussian Processes, heterogeneous learning, and their application to computational Biology and computational social science. She did her first post-doctoral training in Prof. Samuel Kaski's Probabilistic Machine Learning group at Aalto University (2016.01-2019.02), working on developing distributed Bayesian matrix factorization models for large-scale multi-view Chemogenomics data. She then joined FIMM as a postdoctoral researcher in Prof. Tero Aittokallio's group, focusing on developing multiple kernel learning and Bayesian matrix factorisation models to integrate multi-omics data for predicting drug-target responses and identifying predictive bio-markers for pan-cancer.
Sanna completed her Master’s thesis in Olli Kallioniemi’s group at FIMM and graduated in 2014 from the University of Helsinki with a Master of Science in Biology. After her graduation she worked as a laboratory technician, first at the Curie Institute in France (2014-2015), and then at the High-throughput Biomedicine Unit (2015-2016) as well as Tero Aittokallio’s research group (2015-2018) at FIMM. In 2019 she enrolled in PhD training under the supervision of Prof. Tero Aittokallio and Prof. Satu Mustjoki. Sanna’s research aims to find novel individualized therapies for T-cell prolymphocytic leukemia patients by high-throughput drug screening, CRISPR-Cas9 experiments and meta-analyses.
FIMM-HIIT Doctoral Student
Tian received his B.Eng. in pharmaceutical engineering in 2015, and then M.Sc. in pharmacoinformatics in 2018. Tian was enrolled as FIMM/HIIT-EMBL doctoral student in August 2018. He then did rotations in groups at both FIMM and Aalto University. Tian is currently under joint supervision of Prof. Tero Aittokallio, Prof. Juho Rousu, and Prof. Esa Pitkänen. His research focus is to apply machine learning to multi-omics data, to understand mechanisms of complex diseases.
Weikaixin Kong received his Bachelor degree (2015-2019) and Master degree (2019-2021) in Pharmaceutical Sciences in Peking University. In 2021, he joined Tero Aittokallio's group at FIMM as a doctoral student. His research focus is to develop and apply machine learning methods to predict effective and safe drug combinations or survival differences among leukemia patients, with the medical aim to explore and better understand the disease mechanisms of leukemias and to develop robust multi-omics signatures for prognostic and treatment prediction.
- Liye He: Computational tools for high-throughput drug combination screening, synergy scoring and predictive modelling in cancer (2020)
- Balaguru Ravikumar: Computational frameworks to aid pharmacological studies: tools, databases and prediction models (2020)
- Teemu Daniel Laajala: Modeling and prediction of advanced prostate cancer (2019)
- Anna Cichonska: Machine Learning for systems pharmacology (2018)
- Alok Jaiswal: Integrative bioinformatics of functional and genomic profiles for cancer systems medicine (2018)
- Agnieszka Szwajda: Bioinformatic identification of disease driver networks using functional profiling data (2018)
- Prson Gautam: Chemical systems biology studies of triple negative breast cancer cell lines (2017)
- Bhagwan Yadav: Quantitative modeling and analysis of drug screening data for personalized cancer medicine (2017)