Statistical Modeling Methodology on Boolean Functions for Conquering Cancer Complex Ecosystem

2021 Fiscal Year Final Research Report

• Project/Area Number: 18K18151
• Research Category: Grant-in-Aid for Early-Career Scientists
• Allocation Type: Multi-year Fund
• Review Section: Basic Section 62010:Life, health and medical informatics-related
• Research Institution: Nagoya University
• Principal Investigator: Matsui Yusuke 名古屋大学, 医学系研究科(保健), 准教授 (90761495)
• Project Period (FY): 2018-04-01 – 2022-03-31
• Keywords: がんサブクローン進化 / Cancer hallmark / タンパク質複合体 / 共発現変動

Outline of Final Research Achievements

We have developed two main algorithms to approach the complex ecosystem of cancer. One is the estimation algorithm for cancer evolutionary structure at the pathway level using causal inference, and the other is a prediction algorithm for the causal factor causing protein complex deregulation and an approach for estimating mutation effects. These were applied to actual large-scale cancer omics cohort data to confirm their usefulness.

Free Research Field

統計科学、生命情報学、計算生物学、情報科学

Academic Significance and Societal Importance of the Research Achievements

がんの進展に関わる複雑な生物学的現象を数理的にモデリングしていくことで、網羅的な解析のみでは理解できないがんシステムの複雑性を理解でき、がんのフェノタイプを規定する原因同定や薬剤候補スクリーニングへの応用が期待できる。