Haruki Yamane

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データサイエンティスト / ブロックチェーンエンジニア

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Haruki Yamane

大学・大学院で情報工学を専攻し、現在はデータサイエンティストとして活動しております。

Career

Research

Prediction of class A GPCRs and olfactory receptors activity

helixencoder

Olfactory receptors are a type of G protein-coupled receptor (GPCR) that is expressed in the olfactory epithelium and closely associated with the perception of odors. Discovering ligands for olfactory receptors has contributed to unraveling the mechanisms of olfactory perception and has potential implications for drug discovery targeting these receptors. Biological experiments and computational studies for activity prediction have been conducted thus far. To address the challenge of insufficient data for olfactory receptors, this study focused on class A GPCRs and developed a specialized protein sequence encoder called the Helix encoder. Pre-training of the activity prediction model was performed using data from class A GPCRs, followed by fine-tuning using olfactory receptor data, with the aim of improving the accuracy of activity prediction.

Publications

  1. Haruki Yamane and Takashi Ishida. Helix encoder: a compound-protein interaction prediction model specifically designed for class A GPCRs. Frontiers in Bioinformatics, Vol. 3, May 2023.
  2. Haruki Yamane and Takashi Ishida. Prediction of class A GPCR-Compound interactions by deep learning focusing on ligand binding site protein sequences. Chem-Bio Informatics Society(CBI) Annual Meeting 2022, Oct.
  3. 山根 永暉, 石田 貴士. クラスA Gタンパク質共役受容体専用エンコーダを用いたタンパク質ー化合物相互作用予測. 第69回バイオ情報学(SIGBIO)研究会.

Works

株式会社サイシード

株式会社リードエッジコンサルティング

ヤフー株式会社

株式会社プラチナエッグ

Activity

Development

PrimeNumberLoot

pnl