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
1.4k
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
7.6k
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
8.8k
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
1.1k
Other Decks in Research
See All in Research
最近のVisual Odometryと Depth Estimation
sgk
1
240
Weekly AI Agents News! 7月号 プロダクト/ニュースのアーカイブ
masatoto
0
140
Weekly AI Agents News! 6月号 論文のアーカイブ
masatoto
1
170
「Goトレ」のご紹介
smartfukushilab1
0
630
Isotropy, Clusters, and Classifiers
hpprc
3
560
SSII2024 [OS1] 画像認識におけるモデル・データの共進化
ssii
PRO
0
500
MIRU2024チュートリアル「様々なセンサやモダリティを用いたシーン状態推定」
miso2024
3
2.1k
Weekly AI Agents News!
masatoto
22
20k
WikipediaやYouTubeにおける論文参照 / joss2024
corgies
1
260
SSII2024 [OS1] 研究紹介100連発(オープンニング)
ssii
PRO
0
490
CVPR2024論文紹介:Segmentation
hinako0123
0
140
Matching 2D Images in 3D: Metric Relative Pose from Metric Correspondences
sgk
1
280
Featured
See All Featured
In The Pink: A Labor of Love
frogandcode
139
22k
Documentation Writing (for coders)
carmenintech
65
4.4k
Visualization
eitanlees
143
15k
Designing for humans not robots
tammielis
249
25k
実際に使うSQLの書き方 徹底解説 / pgcon21j-tutorial
soudai
167
49k
Intergalactic Javascript Robots from Outer Space
tanoku
268
27k
Git: the NoSQL Database
bkeepers
PRO
425
64k
JavaScript: Past, Present, and Future - NDC Porto 2020
reverentgeek
46
4.9k
Designing on Purpose - Digital PM Summit 2013
jponch
114
6.9k
Become a Pro
speakerdeck
PRO
24
4.9k
4 Signs Your Business is Dying
shpigford
180
21k
How STYLIGHT went responsive
nonsquared
95
5.1k
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