Construction of an Ethanol-Tolerant Yeast Model using the E-cell System. - Mayumi Kamada; Natsu Nakajima; Chisato Ishikawa; Masami Takata; Kazuki Joe (PDPTA, 2008)

Clustering the Temporal Sequences Feature of 3D Protein Structure. - Mayumi Kamada; Sachi Kimura; Mikito Toda; Masami Takata; Kazuki Joe (PDPTA, 2009)

Prediction using step-wise L1, L2 regularization and feature selection for small data sets with large number of features. - Ozgur Demir-Kavuk; Mayumi Kamada; Tatsuya Akutsu; Ernst-Walter Knapp (BMC Bioinform., 2011)

Conditional random field approach to prediction of protein-protein interactions using domain information. - Morihiro Hayashida; Mayumi Kamada; Jiangning Song; Tatsuya Akutsu (BMC Syst. Biol., 2011)

Predicting protein-RNA residue-base contacts using two-dimensional conditional random field. - Morihiro Hayashida; Mayumi Kamada; Jiangning Song; Tatsuya Akutsu (ISB, 2012)

Prediction of protein-RNA residue-base contacts using two-dimensional conditional random field with the lasso. - Morihiro Hayashida; Mayumi Kamada; Jiangning Song; Tatsuya Akutsu (BMC Syst. Biol., 2013)

Construction of Knowledge-Base for Clinical Interpretation of Genomic Variants. - Mayumi Kamada; Toshiaki Katayama; Shuichi Kawashima; Ryosuke Kojima; Masahiko Nakatsui; Yasushi Okuno (SWAT4LS, 2017)

Improving conditional random field model for prediction of protein-RNA residue-base contacts. - Morihiro Hayashida; Noriyuki Okada; Mayumi Kamada; Hitoshi Koyano (Quant. Biol., 2018)

Med2RDF: Semantic Biomedical Knowledge-base and APIs for the Clinical Genome Medicine. - Mayumi Kamada; Toshiaki Katayama; Shuichi Kawashima; Ryosuke Kojima; Masahiko Nakatsui; Yasushi Okuno (SWAT4HCLS, 2019)

Toward more accurate prediction of caspase cleavage sites: a comprehensive review of current methods, tools and features. - Yu Bao; Simone Marini; Takeyuki Tamura; Mayumi Kamada; Shingo Maegawa; Hiroshi Hosokawa; Jiangning Song; Tatsuya Akutsu (Briefings Bioinform., 2019)

GraphIX: Graph-based In silico XAI(explainable artificial intelligence) for drug repositioning from biopharmaceutical network. - Atsuko Takagi; Mayumi Kamada; Eri Hamatani; Ryosuke Kojima; Yasushi Okuno (CoRR, 2022)

An end-to-end framework for gene expression classification by integrating a background knowledge graph: application to cancer prognosis prediction. - Kazuma Inoue; Ryosuke Kojima; Mayumi Kamada; Yasushi Okuno (CoRR, 2023)

A New Deep State-Space Analysis Framework for Patient Latent State Estimation and Classification from EHR Time Series Data. - Aya Nakamura; Ryosuke Kojima; Yuji Okamoto; Eiichiro Uchino; Yohei Mineharu; Yohei Harada; Mayumi Kamada; Manabu Muto; Motoko Yanagita; Yasushi Okuno (CoRR, 2023)

Network-based prediction approach for cancer-specific driver missense mutations using a graph neural network. - Narumi Hatano; Mayumi Kamada; Ryosuke Kojima; Yasushi Okuno (BMC Bioinform., 2023)