Upgrade to Pro
— share decks privately, control downloads, hide ads and more …
Speaker Deck
Features
Speaker Deck
PRO
Sign in
Sign up for free
Search
Search
コンペティションから見るAI創薬/AI drug discovery in the view ...
Search
m_mochizuki
March 18, 2019
Research
2
1.6k
コンペティションから見るAI創薬/AI drug discovery in the view of competitions
日本オミックス医学会シンポジウム 発表資料
場所: 東京医科歯科大学
日付: 2019/3/18
2018/3/20 誤記修正
2018/3/21 誤記修正
m_mochizuki
March 18, 2019
Tweet
Share
More Decks by m_mochizuki
See All by m_mochizuki
SIGNATE: 日本取引所グループ ファンダメンタルズ分析チャレンジ 1位解法 / the 1st place solution of JPX Fundamentals Analysis Challenge on SIGNATE
m_mochizuki
4
13k
SIGNATE: 日本取引所グループ ファンダメンタルズ分析チャレンジ 暫定1位解法 / the provisional 1st place solution of JPX Fundamentals Analysis Challenge on SIGNATE
m_mochizuki
3
9.6k
MD-DSC研究会講演資料:『機械学習コンペティションの実際とその意義』/ Practice on ML competition and its significance
m_mochizuki
1
1.2k
Other Decks in Research
See All in Research
ドメイン知識がない領域での自然言語処理の始め方
hargon24
1
230
その推薦システムの評価指標、ユーザーの感覚とズレてるかも
kuri8ive
1
300
Mamba-in-Mamba: Centralized Mamba-Cross-Scan in Tokenized Mamba Model for Hyperspectral Image Classification
satai
3
420
GPUを利用したStein Particle Filterによる点群6自由度モンテカルロSLAM
takuminakao
0
780
[Devfest Incheon 2025] 모두를 위한 친절한 언어모델(LLM) 학습 가이드
beomi
2
1.4k
湯村研究室の紹介2025 / yumulab2025
yumulab
0
280
LLM-jp-3 and beyond: Training Large Language Models
odashi
1
740
"主観で終わらせない"定性データ活用 ― プロダクトディスカバリーを加速させるインサイトマネジメント / Utilizing qualitative data that "doesn't end with subjectivity" - Insight management that accelerates product discovery
kaminashi
15
18k
Multi-Agent Large Language Models for Code Intelligence: Opportunities, Challenges, and Research Directions
fatemeh_fard
0
120
競合や要望に流されない─B2B SaaSでミニマム要件を決めるリアルな取り組み / Don't be swayed by competitors or requests - A real effort to determine minimum requirements for B2B SaaS
kaminashi
0
450
空間音響処理における物理法則に基づく機械学習
skoyamalab
0
160
Pythonでジオを使い倒そう! 〜それとFOSS4G Hiroshima 2026のご紹介を少し〜
wata909
0
1.2k
Featured
See All Featured
個人開発の失敗を避けるイケてる考え方 / tips for indie hackers
panda_program
122
21k
RailsConf & Balkan Ruby 2019: The Past, Present, and Future of Rails at GitHub
eileencodes
141
34k
Primal Persuasion: How to Engage the Brain for Learning That Lasts
tmiket
0
200
Bridging the Design Gap: How Collaborative Modelling removes blockers to flow between stakeholders and teams @FastFlow conf
baasie
0
420
The Success of Rails: Ensuring Growth for the Next 100 Years
eileencodes
47
7.9k
Fight the Zombie Pattern Library - RWD Summit 2016
marcelosomers
234
17k
Fireside Chat
paigeccino
41
3.8k
Understanding Cognitive Biases in Performance Measurement
bluesmoon
32
2.8k
Ruling the World: When Life Gets Gamed
codingconduct
0
120
Beyond borders and beyond the search box: How to win the global "messy middle" with AI-driven SEO
davidcarrasco
0
33
技術選定の審美眼(2025年版) / Understanding the Spiral of Technologies 2025 edition
twada
PRO
115
100k
Marketing to machines
jonoalderson
1
4.5k
Transcript
a I ( M A M89 :) 3 /21 1
/ 0/ ) ) A c
s ( 21 1- 40 z ( u 76 6
7 ) ) h o 7M M AI( : 7 r a ( k c 7 i
3 IS o J P 123 32 0 J P
T 0 J P T 0 J P T 6 n 0 J P T 4 DJ PG C A 7E5 D4J A C C eB E5
P GI gGI M ci 06?5:
0 65A 4? 5 B C 84 6 76 .?4 8 11ae h M ci 2 3 gM N M ci g T M
6 AI= +.9<*!%;7BG =?4D +.1:/"(&#*
5C0 A, "(&$ = %&' )6F5C=? >@8E3 -23
<; .%7 FC*
'4 <;p53L. + '&(AE!1IBM) DK5=(FC*'40 BH1G .%7D/:36I (-"8$) .%7>@1G JD ↑ # 2?, )9
1
1 0 0 n RAK ) S2 AK K n
g 1 0 Ra Ra 0 5 Q e ( 425 %10/7& (! * , 10/(! $%)+.# # " 425 'Kaggle(063(-
1 n eh a kGn f R / :/ V
Fod eh aFH lm g Sb RHMS A n V . :/ i eh a cS A p 2 / /: / ./: :.
M ,1 42 , 2 , 0 0 9 22
3. n ? n : AC
None
4 1 #)$ ' !%( * $
(Convolutional Neural Network) $ %" & &
1 $)& (" Fingerprint/Descriptor % & (Graph
Convolutional Neural Network) & ! # ' '
n 1 G 6 C n N : Altae-Tran et
al, ACS Cent. Sci.,2017,3(4), pp 283–293
n ( ) P O N B A n I
24 0 2 1 1 Virtual screening… 1 2 3
n N G n K C 967 ( #
&).0 *! "%*@ =1;=>* *(400) 4?:<A5).0 “”* */$, 862?3' +(-OK
7 8 T d fng ] N mi a M
hmi ] C [ Ct ep r a 21 . ? 0 ?9 5 ( ) ) ( )( 02 s y , 9 T u CG ] NaY I
( 7 2 Extended Connectivity Fingerprint Functional Connectivity Fingerprint Topological
Torsions Atom Pairs Fingerprint RDKit Fingerprint Avalon fingerprint !fingerprint (6) 70 Random Forest Extremely Randomized Trees Gradient Boosted Trees Multilayer perceptron Support Vector Regression ! $)%(&' (5) 65 = 30# Elastic Net Pfinal Level 0 Level 1 " # 1 2 ) ):
Fingerprint ECFP FCFP TT AP RDK AVLN F-Stacking RF
0.848 0.855 0.816 0.686 0.652 0.722 0.892 ERT 0.869 0.889 0.844 0.798 0.671 0.768 0.907 GBT 0.852 0.864 0.835 0.808 0.733 0.758 0.891 MLP 0.802 0.777 0.623 0.814 0.651 0.712 0.895 SVR 0.856 0.852 0.688 0.763 0.662 0.693 0.877 L-Stacking 0.890 0.911 0.870 0.881 0.799 0.846 0.930 FL-Stacking Level0 ROC-AUC ) 1 ) (0( 72 n 0 3 0 0
2 ( 7 )1)0 3 5
IMSBIO () ( ) 1 8 1 Univ-shizuoka 1 PFDrug ()Preferred Networks 1 kiharalab 1 1 Graph CNN
1 0
38 5 120 n 0 u ”Taklbe : () :.
00 1Tcn n s T n p w Th cn dg I I “ L ing n r P v T ng D n T t p o y 2 8: : .2 1 2 - // /: 0:
)0 3 6 ( 2 1 n Lel an f
LN b i - b i -/) - n U N gc d - s n D - b i ( 1) -1- P t ( 1) ) vo el an (
)0 37 ( 2 1 n 24 9: 9 0
4 n 1 9 9 56 8 2 3 W 2 9 4 O O O !!!
9 21 n e l ( g n K n
) a )
20 2 3 n 3 t 1 o r ru
2 a i 1 o ru ) 2 l1 ru 1es 2 1 r f K2 n (( h g g K2
1 3 n ( ) ) n : )
X 8 T 9 8. A T 9 8. A
T 9 8. A 0 3 T . 9? A 5 2
( • 9) : / 51) 5 • 1 55
5 2 1:023/ 5