Aittokallio, Tero

Searching for Drug Synergy in Complex Dose–Response Landscapes Using an Interaction Potency Model

Yadav, B., Wennerberg, K., Aittokallio, T., & Tang, J. (2015) · Computational and Structural Biotechnology Journal

Computational Drug Discovery MethodsBioinformatics and Genomic Networks

Cited by 845

Methods for High-throughput Drug Combination Screening and Synergy Scoring

He, L., Kulesskiy, E., Saarela, J., Turunen, L., Wennerberg, K., Aittokallio, T., & Tang, J. (2018) · Methods in Molecular Biology

Computational Drug Discovery MethodsCancer Cells and Metastasis

Cited by 232

Integrated drug profiling and CRISPR screening identify essential pathways for CAR T-cell cytotoxicity

Dufva, O., Koski, J., Maliniemi, P., Ianevski, A., Klievink, J., Leitner, J., Pölönen, P., Hohtari, H., Saeed, K., Hannunen, T., et al. (2020) · Blood

CAR-T cell therapy researchProtein Degradation and Inhibitors

Cited by 224

Implementing a Functional Precision Medicine Tumor Board for Acute Myeloid Leukemia

Malani, D., Kumar, A., Brück, O., Kontro, M., Yadav, B., Hellesøy, M., Kuusanmäki, H., Dufva, O., Kankainen, M., Eldfors, S., et al. (2022) · Cancer Discovery

Acute Myeloid Leukemia ResearchCancer Genomics and Diagnostics

Cited by 193

Susceptibility of low-density lipoprotein particles to aggregate depends on particle lipidome, is modifiable, and associates with future cardiovascular deaths

Ruuth, M., Nguyen, S. D., Vihervaara, T., Hilvo, M., Laajala, T. D., Kondadi, P. K., Gisterå, A., Lähteenmäki, H., Kittilä, T., Huusko, J., et al. (2018) · European Heart Journal

Lipoproteins and Cardiovascular HealthAtherosclerosis and Cardiovascular Diseases

Cited by 180

A harmonized meta-knowledgebase of clinical interpretations of somatic genomic variants in cancer

Variant Interpretation for Cancer Consortium, Wagner, A. H., Walsh, B., Mayfield, G., Tamborero, D., Sonkin, D., Krysiak, K., Deu-Pons, J., Duren, R. P., Gao, J., et al. (2020) · Nature Genetics

Genomics and Rare DiseasesCancer Genomics and Diagnostics

Cited by 164

PP2A inhibition is a druggable MEK inhibitor resistance mechanism in KRAS-mutant lung cancer cells

Kauko, O., O’Connor, C. M., Kulesskiy, E., Sangodkar, J., Aakula, A., Izadmehr, S., Yetukuri, L., Yadav, B., Padzik, A., Laajala, T. D., et al. (2018) · Science Translational Medicine

Protein Tyrosine PhosphatasesProtein Kinase Regulation and GTPase Signaling

Cited by 149

Quantitative Subcellular Proteome and Secretome Profiling of Influenza A Virus-Infected Human Primary Macrophages

Lietzén, N., Öhman, T., Rintahaka, J., Julkunen, I., Aittokallio, T., Matikainen, S., & Nyman, T. A. (2011) · PLoS Pathogens

Influenza Virus Research StudiesInflammasome and immune disorders

Cited by 137

Breeze: an integrated quality control and data analysis application for high-throughput drug screening

Potdar, S., Ianevski, A., Mpindi, J.-P., Bychkov, D., Fiere, C., Ianevski, P., Yadav, B., Wennerberg, K., Aittokallio, T., Kallioniemi, O., et al. (2020) · Bioinformatics

Computational Drug Discovery MethodsCell Image Analysis Techniques

Cited by 102

Intra-tissue steroid profiling indicates differential progesterone and testosterone metabolism in the endometrium and endometriosis lesions

Huhtinen, K., Saloniemi-Heinonen, T., Keski-Rahkonen, P., Desai, R., Laajala, D., Ståhle, M., Häkkinen, M. R., Awosanya, M., Suvitie, P., Kujari, H., et al. (2014) · The Journal of Clinical Endocrinology & Metabolism

Endometriosis Research and TreatmentEstrogen and related hormone effects

Cited by 75

Phosphoproteome and drug-response effects mediated by the three protein phosphatase 2A inhibitor proteins CIP2A, SET, and PME-1

Kauko, O., Imanishi, S. Y., Kulesskiy, E., Yetukuri, L., Laajala, T. D., Sharma, M., Pavic, K., Aakula, A., Rupp, C., Jumppanen, M., et al. (2020) · Journal of Biological Chemistry

Protein Tyrosine PhosphatasesProtein Kinase Regulation and GTPase Signaling

Cited by 65

Drug Combinations as a First Line of Defense against Coronaviruses and Other Emerging Viruses

White, J. M., Schiffer, J. T., Bender Ignacio, R. A., Xu, S., Kainov, D., Ianevski, A., Aittokallio, T., Frieman, M., Olinger, G. G., & Polyak, S. J. (2021) · mBio

SARS-CoV-2 and COVID-19 ResearchCOVID-19 Clinical Research Studies

Cited by 64

Label-free quantitative phosphoproteomics with novel pairwise abundance normalization reveals synergistic RAS and CIP2A signaling

Kauko, O., Laajala, T. D., Jumppanen, M., Hintsanen, P., Suni, V., Haapaniemi, P., Corthals, G., Aittokallio, T., Westermarck, J., & Imanishi, S. Y. (2015) · Scientific Reports

Advanced Proteomics Techniques and ApplicationsProtein Kinase Regulation and GTPase Signaling

Cited by 61

Anticancer compound ABT-263 accelerates apoptosis in virus-infected cells and imbalances cytokine production and lowers survival rates of infected mice

Kakkola, L., Denisova, O. V., Tynell, J., Viiliäinen, J., Ysenbaert, T., Matos, R. C., Nagaraj, A., Öhman, T., Kuivanen, S., Paavilainen, H., et al. (2013) · Cell Death & Disease

Cell death mechanisms and regulationInfluenza Virus Research Studies

Cited by 54

Development of HDAC Inhibitors Exhibiting Therapeutic Potential in T-Cell Prolymphocytic Leukemia

Toutah, K., Nawar, N., Timonen, S., Sorger, H., Raouf, Y. S., Bukhari, S., von Jan, J., Ianevski, A., Gawel, J. M., Olaoye, O. O., et al. (2021) · Journal of Medicinal Chemistry

Histone Deacetylase Inhibitors ResearchChronic Lymphocytic Leukemia Research

Cited by 51

Optimized design and analysis of preclinical intervention studies in vivo

Laajala, T. D., Jumppanen, M., Huhtaniemi, R., Fey, V., Kaur, A., Knuuttila, M., Aho, E., Oksala, R., Westermarck, J., Mäkelä, S., et al. (2016) · Scientific Reports

Statistical Methods in Clinical TrialsAnimal testing and alternatives

Cited by 48

Attention-based approach to predict drug–target interactions across seven target superfamilies

Schulman, A., Rousu, J., Aittokallio, T., & Tanoli, Z. (2024) · Bioinformatics

Computational Drug Discovery MethodsMachine Learning in Bioinformatics

Cited by 25

CIP2A promotes T-cell activation and immune response to Listeria monocytogenes infection

Côme, C., Cvrljevic, A., Khan, M. M., Treise, I., Adler, T., Aguilar-Pimentel, J. A., Au-Yeung, B., Sittig, E., Laajala, T. D., Chen, Y., et al. (2016) · PLoS ONE

T-cell and B-cell ImmunologySignaling Pathways in Disease

Cited by 20

Integrated drug profiling and CRISPR screening identify BCR::ABL1-independent vulnerabilities in chronic myeloid leukemia

Adnan Awad, S., Dufva, O., Klievink, J., Karjalainen, E., Ianevski, A., Pietarinen, P., Kim, D., Potdar, S., Wolf, M., Lotfi, K., et al. (2024) · Cell Reports Medicine

Chronic Myeloid Leukemia TreatmentsChronic Lymphocytic Leukemia Research

Cited by 14

Cost-effective survival prediction for patients with advanced prostate cancer using clinical trial and real-world hospital registry datasets

Murtojärvi, M., Halkola, A. S., Airola, A., Laajala, T. D., Mirtti, T., Aittokallio, T., & Pahikkala, T. (2020) · International Journal of Medical Informatics

Statistical Methods and InferenceRadiomics and Machine Learning in Medical Imaging

Cited by 14

Self-supervised learning for DNA sequences with circular dilated convolutional networks

Cheng, L., Yu, T., Aittokallio, T., Corander, J., Khalitov, R., & Yang, Z. (2023) · Neural Networks

Machine Learning in BioinformaticsGenomics and Chromatin Dynamics

Cited by 12