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Using side effects for drug target identification
Using side effects for drug target identification
Lars Juhl Jensen
Using side effects for drug target identification
Using side effects for drug target identification
Lars Juhl Jensen
Using side effects for drug target identification
Using side effects for drug target identification
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Using side effects for drug target identification
Using side effects for drug target identification
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Systems Biology Workshop, Technical University of Denmark, Lyngy, Denmark, May 14-15, 2009
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Predicting novel targets for existing drugs using side effect information
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The project was about the text mining and information extraction from the social media. The objectives were to develop an information extraction method to extract the side effect information of the psychotropic drugs from the social media (www.webmd.com) and to compare these extracted side effects with the ones listed in www.fda.gov.
Automation Extraction of Side Effect Information from Consumer drug reviews
Automation Extraction of Side Effect Information from Consumer drug reviews
Sunil Paudel
Identification of drug targets from side-effect similarity
Identification of drug targets from side-effect similarity
Lars Juhl Jensen
protein-drug binding
Proteinbindingofdrug 150217022700-conversion-gate02
Proteinbindingofdrug 150217022700-conversion-gate02
MANISH KUMAR
Adverse drug reactions
Adverse drug reactions
Gyanendra Raj Joshi
SEP-L1000 is a machine learning webapp to predict drugs / small molecules side effects based on L1000 transcritomics Signature, structure similarity & morphological profiles.
Systems Pharmacology 3: Predicting drug side effects
Systems Pharmacology 3: Predicting drug side effects
Ali Kishk
Bioavailability
Bioavailability
Bioavailability
Prof. Dr. Basavaraj Nanjwade
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Drug addiction
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ovalaz
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Adverse drug reaction 09
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Protein binding
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Manish sharma
drug toxicity
6.drug toxicity and safety
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เอกสารประกอบการสอนวิชาเภสัชบำบัด ๓ (๗๙๑๕๕๑) หัวข้อ Assessment of Adverse drug...
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Sandro Esteves
medicinal chemistry
Prodrug
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antagonist or agonist
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Santosh Gupta
prodrugs an approach to overcome problems related to ADME, for MPharm students sub- modern pharmaceutical and medicinal chemistry branch- quality assurance
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Using side effects for drug target identification
1.
Using side effects
for drug target identification Lars Juhl Jensen
2.
the problem
3.
new uses for
old drugs
4.
drug–drug network
5.
shared target(s)
6.
chemical similarity
7.
Campillos & Kuhn
et al., Science , 2008
8.
Campillos & Kuhn
et al., Science , 2008
9.
similar drugs share
targets
10.
only trivial predictions
11.
the idea
12.
chemical perturbations
13.
phenotypic readouts
14.
drug treatment
15.
side effects
16.
the hard work
17.
information on side
effects
18.
no database
19.
package inserts
20.
Campillos & Kuhn
et al., Science , 2008
21.
text mining
22.
side-effect ontology
23.
backtracking
24.
Campillos & Kuhn
et al., Science , 2008
25.
manual validation
26.
SIDER Kuhn et
al., Molecular Systems Biology , 2010
27.
side-effect correlations
28.
Campillos & Kuhn
et al., Science , 2008
29.
GSC weighting
30.
side-effect frequencies
31.
Campillos & Kuhn
et al., Science , 2008
32.
raw similarity score
33.
Campillos & Kuhn
et al., Science , 2008
34.
p-values
35.
Campillos & Kuhn
et al., Science , 2008
36.
side-effect similarity
37.
chemical similarity
38.
Campillos & Kuhn
et al., Science , 2008
39.
confidence scores
40.
reference set
41.
incomplete databases
42.
text mining
43.
manual validation
44.
MATADOR Günther et
al., Nucleic Acids Research , 2008
45.
Campillos & Kuhn
et al., Science , 2008
46.
the results
47.
drug–drug network
48.
Campillos & Kuhn
et al., Science , 2008
49.
categorization
50.
Campillos & Kuhn
et al., Science , 2008
51.
20 drug–drug pairs
52.
in vitro
binding assays
53.
K i <10
µM for 11 of 20
54.
cell assays
55.
9 of 9
showed activity
56.
the future
57.
link side-effects to
targets
58.
direct target prediction
59.
60.
larsjuhljensen
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