Application to watch the usage video
theme
It provides a comprehensive explanation of key functions based on common analysis themes. Recommended for those who want to understand the flow and overall picture of analysis.
⓪ Introduction
This is a startup guide that explains the screen layout, basic operations, and common functions of Datachemical LAB.
画面構成 / 基本操作 / 共通機能
① Analysis without experimental data (ver. 3)
Assuming that experimental data is not yet available, we explain the operational flow for using Datachemical LAB to perform the following steps: data preparation → visualization → preprocessing → model building → prediction.
1. 仮想サンプル生成 / 実験計画
4. 混合物計算 補足
2. データ可視化 / 混合物計算 / 特徴量変換
3. MI-モデル最適化 / MI予測-回帰分析 / MI予測-ベイズ最適化
② Analysis after collecting experimental data (ver3)
Assuming a case where experimental data has been collected, we explain the operational flow for using Datachemical LAB to perform "advanced visualization → preprocessing → (model building/prediction) → optimal condition search."
1. 欠損値補完 / 低次元化 / クラスタリング
2. 特徴量選択 / パレート最適解
③ Analysis of chemical structure data (ver. 3)
Assuming a case where analysis is performed using chemical structure data, we explain how to use Datachemical LAB to perform preprocessing specific to chemical structure data and generate prediction data.
構造生成 / 記述子計算
function
This section provides individual explanations of functions not included in the analysis themes above. It is recommended for those who want to understand how to operate specific functions after understanding the flow and overall picture of the analysis.
material design
クラス分類-モデル最適化 / クラス分類-予測
モデル最適化-複数Y同時 / MI予測-複数Y同時回帰分析 / MI予測-直接的逆解析
スペクトル
molecular design
試薬データベース-富士フイルム和光純薬
Process Design
ソフトセンサー
異常検知