博士論文
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Integration of read-across and artificial neural network-based QSAR models for predicting systemic toxicity: A case study for valproic acid

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Integration of read-across and artificial neural network-based QSAR models for predicting systemic toxicity: A case study for valproic acid

Persistent ID (NDL)
info:ndljp/pid/11720051
Material type
博士論文
Author
久木, 友花
Publisher
-
Publication date
2020-09-18
Material Format
Digital
Capacity, size, etc.
-
Name of awarding university/degree
東京女子医科大学,博士(医学)
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Notes on use at the National Diet Library

Notes on use

Note (General):

博士(医学) 乙第3091号(主論文の要旨、要約、審査結果の要旨、本文),著者名:Tomoka HISAKI, Maki AIBA née KANEKO, Morihiko HIROTA, Masato MATSUOKAt, Hirokazu KOUZUKI,タイトル:Integration of ...

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    Digital
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Digital

Material Type
博士論文
Author/Editor
久木, 友花
Author Heading
Publication Date
2020-09-18
Publication Date (W3CDTF)
2020-09-18
Alternative Title
リードアクロス及び人工ニューラルネットワークQSARモデルを用いた全身毒性の予測:バルプロ酸のケーススタディ
Degree grantor/type
東京女子医科大学
Date Granted
2020-09-18
Date Granted (W3CDTF)
2020-09-18