SlideShare uma empresa Scribd logo
1 de 44
Baixar para ler offline
Rajarshi	Guha,	NIH-NCATS
LINCS	Data	Science	Research	Webinar	Series
75%	of	protein	research	still	
focused	on	10%	genes	known	
before	human	genome	was	
mapped
AM	Edwards	et	al,	Nature,	2011
This	prompted	NIH	to	start	
the	Illuminating	the	Druggable
Genome	Initiative
The	Need	for	the	IDG
IDG	Knowledge	Management	Center
Target	Development	Level
• Protein	classification	
schemes	are	based	on	
structural	and	functional	
criteria.	
• For	therapeutic	
development,	it	is	useful	
to	understand	how	much	
and	what	types	of	data	
are	available	for	a	given	
protein,	thereby	
highlighting	well-studied	
and	understudied	targets.	
T.	Oprea et	al.,	Nature	Rev.	Drug	Discov.	poster,		Jan	2017
Target	Development	Level
• Proteins	annotated	as	
drug	targets	are	Tclin
• Proteins	for	which	potent	
small	molecules	are	
known	are	Tchem
• Proteins	for	which	biology	
is	better	understood	are	
Tbio
• Proteins	that	lack	
antibodies,	publications	
or	Gene	RIFs	are	Tdark
T.	Oprea et	al.,	Nature	Rev.	Drug	Discov.	poster,		Jan	2017
TDL:	External	Validation
T.	Oprea et	al.,	Nature	Rev.	Drug	Discov.	poster,		Jan	2017
Why	Should	ANYONE	Fund	Tdark?
Data	from	Tudor	Oprea &	Christian	Bologa
Leptin
SMO
S1PR1
Orexin
PCSK9
Ghrelin
1995 2000 2005 2010 2015
Median	time	to	go	from	Tdark	
to	bearing	fruit	is	17	years
The	Causality	Dilemma
• Are	Tdark	proteins	underfunded	because	there	is	
no	scientific	interest	in	this	category,	or	is	the	lack	
of	knowledge	perpetuated	by	lack	of	funding?
• It	is	possible	that	the	absence	of	high	quality,	well	
characterized	molecular	probes	may	be	a	root	
cause	for	this	situation.	
• However,	lack	of	tools	leads	to	lack	of	interest,	and	
lack	of	interest	diminishes	the	probability	of	such	
tools	being	developed
Tudor	Oprea
There	is	a	Knowledge	Deficit
• >	37%	of	proteins	are	poorly	described	(Tdark)
• ~10%	of	the	Proteome	(Tclin	&	Tchem)	can	be	
targeted	by	small	molecules
• 10%	of	NIH	R01’s	(2011-2015)	awarded	to	study	11	
targets	(out	of	7,934	targets	funded	in	total)
• Dark	genes	need	funding	and	patience
https://academic.oup.com/nar/article-lookup/doi/10.1093/nar/gkw1072
Entity	browsing	(filterable	&	linked)Search	(full	text,	auto-suggest)
Detailed	view	of	entities Built	on	top	of	a	robust	REST	API
Pharos	- An	Interface	to	the	KMC
Current	Status191 facets
17.8 GB database
30 GB Lucene indexes
36K LoC (Java)
14K LoC (Scala)
Image available
Source code available
20,120	targets
15,094	diseases
2.3M	publications
4,500	drugs
What’s	Included?
• Pharos	presents	data	from	a	variety	of	sources,	
integrated	by	U.	New	Mexico	
• Primary	focus	is	the	protein	target
• Wherever	possible,	targets	are	linked	to	other	
entities	(which	are	also	interlinked)
• Small	molecules,	Diseases,	Publications	
• Target	related	data	include
• Identifiers,	ontology	terms,	sequence,	expression	data,	
publications	(curated	&	text	mined),	phenotypes,	PPI
Data	Sources
Full	data	source	list	at	http://targetcentral.ws/Pharos
Drug Target Ontology
TCRD
DISEASE
TIN-X
Interactions	inside	&	
outside	the	IDG
Target	Audience
Biologists	&	
Clinical	Researcher
• Characterize	&	
validate	novel	
targets
• Identify	key	small	
molecules	or	
biologics
Informatics	
Scientists
• Data	mining
• Support	target	
validation	
projects
Program	Staff
• Explore	the	
research	
landscape
• New	directions	
for	research &	
funding
Different	Ways	to	Use	Pharos
Random
Access
Direct
Access
Manual Interaction Programmatic Interaction
Search Entity Info
Precomputation converts	analysis	in	to	browsing
Supporting	Both	Types	of	Users
• Efficient	full	text	search,	coupled	to	relevant	auto-
suggestion
• Primary	entry	point	when	exploring	
and	for	hypothesis	generation
• Extensive	list	of	facets
• Supports	easy	construction	of	
complex	filtering	rules
• Extensive	details	for	each	
target
• Linked	to	external	and	
internal resources
Batch	Search
• Easily	pull	up	on	data	on	multiple	targets	at	one	go
Sequence	Search
• Query is	ABL,ARG (from	LINCS	KiNativ dataset),	
similarity	>	0.7
Structure	Search
• Search by	substructure	or	similarity
• Identify	targets	enriched	in	a	scaffold
Visualization
• Key	requirement	for	efficient	exploration,	summary
• Increase	information	density	in	limited	screen	real	
estate,	take	context	into	account
• Interactivity	is	desirable,	high	quality	for	easy	
inclusion	in	documents
• Simple	is	better	than	fancy	but	pretty	pictures	have	
value,	make	for	a	better	experience
• Integrate	and	link	to	external	visualization
• TinX,	Harmonizome
Visualization	Highlights
Visualization	dashboard	– filters	appropriately
represented,	plots	act	as	filters
Inline	visualization	to	increase	information	density
Summary	visualizations	
overlay	multiple	dimensions	
and	can	be	context	aware
Integrating	External	Tools
Tclin,	Kinase
Tdark,	GPCR
Pharos
TinX
Enhanced	Documentation
Entity	Dossier
• As	you	explore	the	knowledge	base	it’s	useful	keep	
track	of	data
• Pharos	implements	a	dossier	function
• Analogous	to	e-commerce	shopping	carts
• Support	for	task-specific	dossiers
• Download	a	dossier	as	a		ZIP	file
Entity	Dossier
Multiple	dossiers
Set	operationsVisualization	tools
Download
Longer	term,	dossiers	will	be	automatically	enriched	with	
linked	items	and	recommendations
Dossiers	as	Context
Overlay	data	from	targets	in	a	dossier
Quantifying	Knowledge	About	Targets
• The	Harmonizome represents	the	data	available	
around	a	given	target
• Compute	the	number	of	associations	for	each	gene	in	
a	data	source	and	convert	to	ECDF
• Precomputed in	TCRD
• Used	by	Harmonogram and	radar	chart	viz
• Define	the	Knowledge	Availability	Score	(KAS)
KAST = Ci
i=1
n
∑
Knowledge	Availability	Score
0
50
100
150
0 20 40 60
Knowledge Availability Score
Frequency
Knowledge	Availability	in	Pharos
KAS	vs.	Other	measures
KAS	vs.	Other	measures
• Best	correlation	with	Pubmed count
• As	expected,	data	for		Tdark is	noisier
• Of	interest	are	those	targets	with	higher	values	of	
knowledge	availability	but	small	values	of	another	
metric
• In	particular	the	Jensen	
Pubmed Score	seems	to	
lead	to	such	targets
1
100
10000
0 20 40 60
Knowledge Availability Score
JensenPubmedScore
Tbio
Tchem
Tclin
Tdark
(Dis)similarity	in	Knowledge	Space
• There	are	114	unique	data	sources	via	the	
Harmonizome
• We	represent	each	target	as	a	114-element	vector
• Where	a	source	has	no	data	for	the	target,	we	set	it's	value	
to	0
• Not	necessarily	the	best	choice,	since	it's	really	missing	
data
• Uniform	weighting	may	not	be	appropriate
• Compute	a	pairwise	Euclidean	distance	matrix	or	
cosine	similarity	matrix	for	1757	targets
Cosine	similarity	in	Knowledge	Space
Similarity	in	Knowledge	Space
• Consider	Euclidean	distance	matrix
• Of	particular	interest	is	to	identify	Tdark targets	
that	have	a	knowledge	profile	that	is	most	similar	
to	targets	that	are	not	Tdark
• 44	such	targets
• Within	this	set,	10	targets	have	a	knowledge	profile	
that	is	most	similar	to	a	Tchem or	Tclin target
Target	Similarity
• Compute	target	
similarity	in	
“Harmonizome space”
• Supports	
recommendations,	
prioritization
• Currently	extending	to	
a	generalized	Target	
Knowledge	Vector	
approach
Tdark targets	whose	most	
similar	target	is	not	Tdark
What	might	this	mean?
• Publications	are	one	way	to	prioritize	targets
• But	we	should	also	consider	the	extent	of	data	
around	targets
• Alternatively,	all	(or	multiple	types	of)		the	data	
about	a	target	is	subsumed	into	a	small	set	of	
publications
• One	paper	might	include	RNAseq,	CNV,	pharmacology	
• Publications	lag	data
• Tdark targets	with	a	(relative)	higher	knowledge	
availability	value	but	low	publication	based	score	
could	be	rising	stars?
Next	Steps	- Target	Knowledge	Vectors
• Based	on	sparse	vector	representation	of	data	
availability,	applied	to	20K	targets
• A	target	is	a	document	mixture	of	discrete	and	
continuous	variable	descriptors
• Set	of	facet	values/terms	and	frequencies
• Amino	acid	sequence	length	and	individual	AA	residue	
profiles
• Counts	of	related	publications,	ligands,	Xtals,	diseases,	
protein-protein	interactions,	etc.
• Similar	to	TD-IDF,	facet	value	frequencies	are	
inversely	weighted	by	popularity
• The	similarity	is	calculated	as	generalized	Tanimoto
Outreach	&	Dissemination	Activities
User Feedback Deployment
Webinars Documentation
NER API for
targets & diseases
@idg_pharos
Recent	papers	to	
Pharos	links	via	
Tweets
Pharos	Usage
• Usage	statistics	over	
the	last	one	year	are	
generally	increasing
• 89K	pageviews
• 14K	sessions
• 7.5K	users
Pharos	Indexing
Now	includes	hits	in	
partner	databases	such	
as	KEGG	and	ChEMBL
The	Long	Term	Vision
• Incorporate	dependencies
between	data	types	to	support
inference	and	sophisticated	filters
• From	presentation	to	summarization
• Use	explicit	links	&	computational	
inference	to	generate	(semi-)	natural	language
summary	using	all	known	data
• Influenced	by	the	query
• The	result	is	a	biological	dashboard,	
customized	for	the	user	and	the	query
Target X has been implicated in 3
diseases related to skeletal, urological
and nervous systems. It has been
investigated in 5 in vitro assay, 2 in
vivo assays. There are 4 compounds
active against this target, 3 of which
are in clinical trials.
Feedback
• Explore	the	UI,	try	it,	break	it,	and	let	us	know	what	
works	and	what	doesn’t
• Are	there	data	types	and	relations	that	would	help	
you	but	are	not	available?
• Nguyen	&	Mathias	et	al,	Nucl.	Acids	Res.,	2017
https://pharos.nih.gov
https://spotlite.nih.gov/pharos
https://hub.docker.com/r/ncats/pharos/
pharos@nih.gov
@idg_pharos
Acknowledgements
• Dac-Trung Nguyen,	Kyle	Brinacombe,	Timothy	
Sheils,	Geetha Mandava,	Noel	Southall,	Ajit Jadhav
• Steve	Mathias,	Oleg	Ursu,	Jeremy	Yang,	Christian	
Bologa,	Daniel	Canon,	Tudor	Oprea
• Nicholas	Fernandez,	Andrew	Rouillard,	Avi Mayan
• Finkbeiner lab,	Tomita	Lab
• Ajay	Pillai,	Aaron	Pawlyk,	Christine	Colvis

Mais conteúdo relacionado

Mais procurados

Research data and scholarly publications: going from casual acquaintances to ...
Research data and scholarly publications: going from casual acquaintances to ...Research data and scholarly publications: going from casual acquaintances to ...
Research data and scholarly publications: going from casual acquaintances to ...Todd Vision
 
Knowledge Exchange, Nov 2011, Bonn
Knowledge Exchange, Nov 2011, BonnKnowledge Exchange, Nov 2011, Bonn
Knowledge Exchange, Nov 2011, BonnTodd Vision
 
Leveraging publication metadata to help overcome the data ingest bottleneck
Leveraging publication metadata to help overcome the data ingest bottleneck Leveraging publication metadata to help overcome the data ingest bottleneck
Leveraging publication metadata to help overcome the data ingest bottleneck Todd Vision
 
Why should researchers care about data curation?
Why should researchers care about data curation?Why should researchers care about data curation?
Why should researchers care about data curation?Varsha Khodiyar
 
Data Mining and Big Data Analytics in Pharma
Data Mining and Big Data Analytics in Pharma Data Mining and Big Data Analytics in Pharma
Data Mining and Big Data Analytics in Pharma Ankur Khanna
 
The Dryad Digital Repository: Published evolutionary data as part of the gre...
The Dryad Digital Repository: Published evolutionary data as part of the gre...The Dryad Digital Repository: Published evolutionary data as part of the gre...
The Dryad Digital Repository: Published evolutionary data as part of the gre...Todd Vision
 
NCBO haendel talk 2013
NCBO haendel talk 2013NCBO haendel talk 2013
NCBO haendel talk 2013mhaendel
 
Semantic Web & Web 3.0 empowering real world outcomes in biomedical research ...
Semantic Web & Web 3.0 empowering real world outcomes in biomedical research ...Semantic Web & Web 3.0 empowering real world outcomes in biomedical research ...
Semantic Web & Web 3.0 empowering real world outcomes in biomedical research ...Amit Sheth
 
A FAIR Data Sharing Framework for Large-Scale Human Cancer Proteogenomics
A FAIR Data Sharing Framework for Large-Scale Human Cancer ProteogenomicsA FAIR Data Sharing Framework for Large-Scale Human Cancer Proteogenomics
A FAIR Data Sharing Framework for Large-Scale Human Cancer ProteogenomicsBrett Tully
 
Pharma data analytics
Pharma data analyticsPharma data analytics
Pharma data analyticsAxon Lawyers
 
tranSMART Community Meeting 5-7 Nov 13 - Session 3: Pfizer’s Recent Use of tr...
tranSMART Community Meeting 5-7 Nov 13 - Session 3: Pfizer’s Recent Use of tr...tranSMART Community Meeting 5-7 Nov 13 - Session 3: Pfizer’s Recent Use of tr...
tranSMART Community Meeting 5-7 Nov 13 - Session 3: Pfizer’s Recent Use of tr...David Peyruc
 
Rii stock centerdir_aug9_2016
Rii stock centerdir_aug9_2016Rii stock centerdir_aug9_2016
Rii stock centerdir_aug9_2016Anita Bandrowski
 
effective data sharing for a learning healthcare system
effective data sharing for a learning healthcare systemeffective data sharing for a learning healthcare system
effective data sharing for a learning healthcare systemPaul Houston
 
Gaining credit for sharing research data
Gaining credit for sharing research dataGaining credit for sharing research data
Gaining credit for sharing research dataVarsha Khodiyar
 
Clinical trial data wants to be free: Lessons from the ImmPort Immunology Dat...
Clinical trial data wants to be free: Lessons from the ImmPort Immunology Dat...Clinical trial data wants to be free: Lessons from the ImmPort Immunology Dat...
Clinical trial data wants to be free: Lessons from the ImmPort Immunology Dat...Barry Smith
 
Considerations and challenges in building an end to-end microbiome workflow
Considerations and challenges in building an end to-end microbiome workflowConsiderations and challenges in building an end to-end microbiome workflow
Considerations and challenges in building an end to-end microbiome workflowEagle Genomics
 
dkNET Poster Experimental Biology 2019
dkNET Poster Experimental Biology 2019dkNET Poster Experimental Biology 2019
dkNET Poster Experimental Biology 2019dkNET
 
Pulverer-embo-source data-nfdp13
Pulverer-embo-source data-nfdp13Pulverer-embo-source data-nfdp13
Pulverer-embo-source data-nfdp13DataDryad
 
Digital transformation of translational medicine
Digital transformation of translational medicineDigital transformation of translational medicine
Digital transformation of translational medicineEagle Genomics
 

Mais procurados (20)

Research data and scholarly publications: going from casual acquaintances to ...
Research data and scholarly publications: going from casual acquaintances to ...Research data and scholarly publications: going from casual acquaintances to ...
Research data and scholarly publications: going from casual acquaintances to ...
 
Knowledge Exchange, Nov 2011, Bonn
Knowledge Exchange, Nov 2011, BonnKnowledge Exchange, Nov 2011, Bonn
Knowledge Exchange, Nov 2011, Bonn
 
Leveraging publication metadata to help overcome the data ingest bottleneck
Leveraging publication metadata to help overcome the data ingest bottleneck Leveraging publication metadata to help overcome the data ingest bottleneck
Leveraging publication metadata to help overcome the data ingest bottleneck
 
Why should researchers care about data curation?
Why should researchers care about data curation?Why should researchers care about data curation?
Why should researchers care about data curation?
 
Data Mining and Big Data Analytics in Pharma
Data Mining and Big Data Analytics in Pharma Data Mining and Big Data Analytics in Pharma
Data Mining and Big Data Analytics in Pharma
 
The Dryad Digital Repository: Published evolutionary data as part of the gre...
The Dryad Digital Repository: Published evolutionary data as part of the gre...The Dryad Digital Repository: Published evolutionary data as part of the gre...
The Dryad Digital Repository: Published evolutionary data as part of the gre...
 
NCBO haendel talk 2013
NCBO haendel talk 2013NCBO haendel talk 2013
NCBO haendel talk 2013
 
Semantic Web & Web 3.0 empowering real world outcomes in biomedical research ...
Semantic Web & Web 3.0 empowering real world outcomes in biomedical research ...Semantic Web & Web 3.0 empowering real world outcomes in biomedical research ...
Semantic Web & Web 3.0 empowering real world outcomes in biomedical research ...
 
A FAIR Data Sharing Framework for Large-Scale Human Cancer Proteogenomics
A FAIR Data Sharing Framework for Large-Scale Human Cancer ProteogenomicsA FAIR Data Sharing Framework for Large-Scale Human Cancer Proteogenomics
A FAIR Data Sharing Framework for Large-Scale Human Cancer Proteogenomics
 
MPS webinar master deck
MPS webinar master deckMPS webinar master deck
MPS webinar master deck
 
Pharma data analytics
Pharma data analyticsPharma data analytics
Pharma data analytics
 
tranSMART Community Meeting 5-7 Nov 13 - Session 3: Pfizer’s Recent Use of tr...
tranSMART Community Meeting 5-7 Nov 13 - Session 3: Pfizer’s Recent Use of tr...tranSMART Community Meeting 5-7 Nov 13 - Session 3: Pfizer’s Recent Use of tr...
tranSMART Community Meeting 5-7 Nov 13 - Session 3: Pfizer’s Recent Use of tr...
 
Rii stock centerdir_aug9_2016
Rii stock centerdir_aug9_2016Rii stock centerdir_aug9_2016
Rii stock centerdir_aug9_2016
 
effective data sharing for a learning healthcare system
effective data sharing for a learning healthcare systemeffective data sharing for a learning healthcare system
effective data sharing for a learning healthcare system
 
Gaining credit for sharing research data
Gaining credit for sharing research dataGaining credit for sharing research data
Gaining credit for sharing research data
 
Clinical trial data wants to be free: Lessons from the ImmPort Immunology Dat...
Clinical trial data wants to be free: Lessons from the ImmPort Immunology Dat...Clinical trial data wants to be free: Lessons from the ImmPort Immunology Dat...
Clinical trial data wants to be free: Lessons from the ImmPort Immunology Dat...
 
Considerations and challenges in building an end to-end microbiome workflow
Considerations and challenges in building an end to-end microbiome workflowConsiderations and challenges in building an end to-end microbiome workflow
Considerations and challenges in building an end to-end microbiome workflow
 
dkNET Poster Experimental Biology 2019
dkNET Poster Experimental Biology 2019dkNET Poster Experimental Biology 2019
dkNET Poster Experimental Biology 2019
 
Pulverer-embo-source data-nfdp13
Pulverer-embo-source data-nfdp13Pulverer-embo-source data-nfdp13
Pulverer-embo-source data-nfdp13
 
Digital transformation of translational medicine
Digital transformation of translational medicineDigital transformation of translational medicine
Digital transformation of translational medicine
 

Semelhante a Pharos – A Torch to Use in Your Journey In the Dark Genome

NIH Drug Discovery and Development - NCTT and CTSAs
NIH Drug Discovery and Development - NCTT and CTSAsNIH Drug Discovery and Development - NCTT and CTSAs
NIH Drug Discovery and Development - NCTT and CTSAsCTSI at UCSF
 
FAIRness and Accountability BioIT 2019 FAIR track
FAIRness and Accountability BioIT 2019 FAIR trackFAIRness and Accountability BioIT 2019 FAIR track
FAIRness and Accountability BioIT 2019 FAIR trackHelena Deus
 
The Translational Medicine
The Translational MedicineThe Translational Medicine
The Translational MedicineJoanne Luciano
 
The Learning Health System: Thinking and Acting Across Scales
The Learning Health System: Thinking and Acting Across ScalesThe Learning Health System: Thinking and Acting Across Scales
The Learning Health System: Thinking and Acting Across ScalesPhilip Payne
 
MedicalResearch.com: Medical Research Exclusive Interviews July 2 2015
MedicalResearch.com:  Medical Research Exclusive Interviews July 2 2015MedicalResearch.com:  Medical Research Exclusive Interviews July 2 2015
MedicalResearch.com: Medical Research Exclusive Interviews July 2 2015Marie Benz MD FAAD
 
MedicalResearch.com: Medical Research Exclusive Interviews January 7 2014
MedicalResearch.com:  Medical Research Exclusive Interviews January 7  2014MedicalResearch.com:  Medical Research Exclusive Interviews January 7  2014
MedicalResearch.com: Medical Research Exclusive Interviews January 7 2014Marie Benz MD FAAD
 
6-005-1430-Keeppanasseril
6-005-1430-Keeppanasseril6-005-1430-Keeppanasseril
6-005-1430-Keeppanasserilmed20su
 
dkNET Webinar: Illuminating The Druggable Genome With Pharos 10/23/2020
dkNET Webinar: Illuminating The Druggable Genome With Pharos 10/23/2020dkNET Webinar: Illuminating The Druggable Genome With Pharos 10/23/2020
dkNET Webinar: Illuminating The Druggable Genome With Pharos 10/23/2020dkNET
 
Restorative Therapies for Erectile Dysfunction
Restorative Therapies for Erectile Dysfunction Restorative Therapies for Erectile Dysfunction
Restorative Therapies for Erectile Dysfunction Ranjith Ramasamy
 
Nlp for the precision medicine
Nlp for the precision medicineNlp for the precision medicine
Nlp for the precision medicineVishwas N
 
Scope and Applications of Bioinformatics --Nishikant Bhojane.pptx
Scope and Applications of Bioinformatics --Nishikant Bhojane.pptxScope and Applications of Bioinformatics --Nishikant Bhojane.pptx
Scope and Applications of Bioinformatics --Nishikant Bhojane.pptxNishikantBhojane1
 
Drug discovery and development overview
Drug discovery and development overviewDrug discovery and development overview
Drug discovery and development overviewSunil Boreddy Rx
 
Epigen Biosciences I-Corps@NIH 121014
Epigen Biosciences I-Corps@NIH 121014Epigen Biosciences I-Corps@NIH 121014
Epigen Biosciences I-Corps@NIH 121014Stanford University
 
Mobilizing informational resources webinar
Mobilizing informational resources   webinarMobilizing informational resources   webinar
Mobilizing informational resources webinarAnn-Marie Roche
 
medical-test-reviews-genetic.ppt
medical-test-reviews-genetic.pptmedical-test-reviews-genetic.ppt
medical-test-reviews-genetic.pptssuser2cad2a
 
Predictive analytics for personalized healthcare
Predictive analytics for personalized healthcarePredictive analytics for personalized healthcare
Predictive analytics for personalized healthcareJohn Cai
 

Semelhante a Pharos – A Torch to Use in Your Journey In the Dark Genome (20)

NIH Drug Discovery and Development - NCTT and CTSAs
NIH Drug Discovery and Development - NCTT and CTSAsNIH Drug Discovery and Development - NCTT and CTSAs
NIH Drug Discovery and Development - NCTT and CTSAs
 
FAIRness and Accountability BioIT 2019 FAIR track
FAIRness and Accountability BioIT 2019 FAIR trackFAIRness and Accountability BioIT 2019 FAIR track
FAIRness and Accountability BioIT 2019 FAIR track
 
Opensourcepharma Dr Nibedita rath
Opensourcepharma Dr Nibedita rathOpensourcepharma Dr Nibedita rath
Opensourcepharma Dr Nibedita rath
 
The Translational Medicine
The Translational MedicineThe Translational Medicine
The Translational Medicine
 
The Learning Health System: Thinking and Acting Across Scales
The Learning Health System: Thinking and Acting Across ScalesThe Learning Health System: Thinking and Acting Across Scales
The Learning Health System: Thinking and Acting Across Scales
 
MedicalResearch.com: Medical Research Exclusive Interviews July 2 2015
MedicalResearch.com:  Medical Research Exclusive Interviews July 2 2015MedicalResearch.com:  Medical Research Exclusive Interviews July 2 2015
MedicalResearch.com: Medical Research Exclusive Interviews July 2 2015
 
Atul Butte NIPS 2017 ML4H
Atul Butte NIPS 2017 ML4HAtul Butte NIPS 2017 ML4H
Atul Butte NIPS 2017 ML4H
 
MedicalResearch.com: Medical Research Exclusive Interviews January 7 2014
MedicalResearch.com:  Medical Research Exclusive Interviews January 7  2014MedicalResearch.com:  Medical Research Exclusive Interviews January 7  2014
MedicalResearch.com: Medical Research Exclusive Interviews January 7 2014
 
6-005-1430-Keeppanasseril
6-005-1430-Keeppanasseril6-005-1430-Keeppanasseril
6-005-1430-Keeppanasseril
 
dkNET Webinar: Illuminating The Druggable Genome With Pharos 10/23/2020
dkNET Webinar: Illuminating The Druggable Genome With Pharos 10/23/2020dkNET Webinar: Illuminating The Druggable Genome With Pharos 10/23/2020
dkNET Webinar: Illuminating The Druggable Genome With Pharos 10/23/2020
 
Restorative Therapies for Erectile Dysfunction
Restorative Therapies for Erectile Dysfunction Restorative Therapies for Erectile Dysfunction
Restorative Therapies for Erectile Dysfunction
 
Evidence based Practice in Emergency Medicine
Evidence based Practice in Emergency Medicine Evidence based Practice in Emergency Medicine
Evidence based Practice in Emergency Medicine
 
Nlp for the precision medicine
Nlp for the precision medicineNlp for the precision medicine
Nlp for the precision medicine
 
Scope and Applications of Bioinformatics --Nishikant Bhojane.pptx
Scope and Applications of Bioinformatics --Nishikant Bhojane.pptxScope and Applications of Bioinformatics --Nishikant Bhojane.pptx
Scope and Applications of Bioinformatics --Nishikant Bhojane.pptx
 
Drug discovery and development overview
Drug discovery and development overviewDrug discovery and development overview
Drug discovery and development overview
 
Epigen Biosciences I-Corps@NIH 121014
Epigen Biosciences I-Corps@NIH 121014Epigen Biosciences I-Corps@NIH 121014
Epigen Biosciences I-Corps@NIH 121014
 
Mobilizing informational resources webinar
Mobilizing informational resources   webinarMobilizing informational resources   webinar
Mobilizing informational resources webinar
 
Ebm
EbmEbm
Ebm
 
medical-test-reviews-genetic.ppt
medical-test-reviews-genetic.pptmedical-test-reviews-genetic.ppt
medical-test-reviews-genetic.ppt
 
Predictive analytics for personalized healthcare
Predictive analytics for personalized healthcarePredictive analytics for personalized healthcare
Predictive analytics for personalized healthcare
 

Mais de Rajarshi Guha

Pharos - Face of the KMC
Pharos - Face of the KMCPharos - Face of the KMC
Pharos - Face of the KMCRajarshi Guha
 
Enhancing Prioritization & Discovery of Novel Combinations using an HTS Platform
Enhancing Prioritization & Discovery of Novel Combinations using an HTS PlatformEnhancing Prioritization & Discovery of Novel Combinations using an HTS Platform
Enhancing Prioritization & Discovery of Novel Combinations using an HTS PlatformRajarshi Guha
 
What can your library do for you?
What can your library do for you?What can your library do for you?
What can your library do for you?Rajarshi Guha
 
So I have an SD File … What do I do next?
So I have an SD File … What do I do next?So I have an SD File … What do I do next?
So I have an SD File … What do I do next?Rajarshi Guha
 
Characterization of Chemical Libraries Using Scaffolds and Network Models
Characterization of Chemical Libraries Using Scaffolds and Network ModelsCharacterization of Chemical Libraries Using Scaffolds and Network Models
Characterization of Chemical Libraries Using Scaffolds and Network ModelsRajarshi Guha
 
From Data to Action : Bridging Chemistry and Biology with Informatics at NCATS
From Data to Action: Bridging Chemistry and Biology with Informatics at NCATSFrom Data to Action: Bridging Chemistry and Biology with Informatics at NCATS
From Data to Action : Bridging Chemistry and Biology with Informatics at NCATSRajarshi Guha
 
Robots, Small Molecules & R
Robots, Small Molecules & RRobots, Small Molecules & R
Robots, Small Molecules & RRajarshi Guha
 
Fingerprinting Chemical Structures
Fingerprinting Chemical StructuresFingerprinting Chemical Structures
Fingerprinting Chemical StructuresRajarshi Guha
 
Exploring Compound Combinations in High Throughput Settings: Going Beyond 1D...
Exploring Compound Combinations in High Throughput Settings: Going Beyond 1D...Exploring Compound Combinations in High Throughput Settings: Going Beyond 1D...
Exploring Compound Combinations in High Throughput Settings: Going Beyond 1D...Rajarshi Guha
 
When the whole is better than the parts
When the whole is better than the partsWhen the whole is better than the parts
When the whole is better than the partsRajarshi Guha
 
Exploring Compound Combinations in High Throughput Settings: Going Beyond 1D ...
Exploring Compound Combinations in High Throughput Settings: Going Beyond 1D ...Exploring Compound Combinations in High Throughput Settings: Going Beyond 1D ...
Exploring Compound Combinations in High Throughput Settings: Going Beyond 1D ...Rajarshi Guha
 
Pushing Chemical Biology Through the Pipes
Pushing Chemical Biology Through the PipesPushing Chemical Biology Through the Pipes
Pushing Chemical Biology Through the PipesRajarshi Guha
 
Characterization and visualization of compound combination responses in a hig...
Characterization and visualization of compound combination responses in a hig...Characterization and visualization of compound combination responses in a hig...
Characterization and visualization of compound combination responses in a hig...Rajarshi Guha
 
The BioAssay Research Database
The BioAssay Research DatabaseThe BioAssay Research Database
The BioAssay Research DatabaseRajarshi Guha
 
Cloudy with a Touch of Cheminformatics
Cloudy with a Touch of CheminformaticsCloudy with a Touch of Cheminformatics
Cloudy with a Touch of CheminformaticsRajarshi Guha
 
Chemical Data Mining: Open Source & Reproducible
Chemical Data Mining: Open Source & ReproducibleChemical Data Mining: Open Source & Reproducible
Chemical Data Mining: Open Source & ReproducibleRajarshi Guha
 
Chemogenomics in the cloud: Is the sky the limit?
Chemogenomics in the cloud: Is the sky the limit?Chemogenomics in the cloud: Is the sky the limit?
Chemogenomics in the cloud: Is the sky the limit?Rajarshi Guha
 
Quantifying Text Sentiment in R
Quantifying Text Sentiment in RQuantifying Text Sentiment in R
Quantifying Text Sentiment in RRajarshi Guha
 
PMML for QSAR Model Exchange
PMML for QSAR Model Exchange PMML for QSAR Model Exchange
PMML for QSAR Model Exchange Rajarshi Guha
 

Mais de Rajarshi Guha (20)

Pharos - Face of the KMC
Pharos - Face of the KMCPharos - Face of the KMC
Pharos - Face of the KMC
 
Enhancing Prioritization & Discovery of Novel Combinations using an HTS Platform
Enhancing Prioritization & Discovery of Novel Combinations using an HTS PlatformEnhancing Prioritization & Discovery of Novel Combinations using an HTS Platform
Enhancing Prioritization & Discovery of Novel Combinations using an HTS Platform
 
What can your library do for you?
What can your library do for you?What can your library do for you?
What can your library do for you?
 
So I have an SD File … What do I do next?
So I have an SD File … What do I do next?So I have an SD File … What do I do next?
So I have an SD File … What do I do next?
 
Characterization of Chemical Libraries Using Scaffolds and Network Models
Characterization of Chemical Libraries Using Scaffolds and Network ModelsCharacterization of Chemical Libraries Using Scaffolds and Network Models
Characterization of Chemical Libraries Using Scaffolds and Network Models
 
From Data to Action : Bridging Chemistry and Biology with Informatics at NCATS
From Data to Action: Bridging Chemistry and Biology with Informatics at NCATSFrom Data to Action: Bridging Chemistry and Biology with Informatics at NCATS
From Data to Action : Bridging Chemistry and Biology with Informatics at NCATS
 
Robots, Small Molecules & R
Robots, Small Molecules & RRobots, Small Molecules & R
Robots, Small Molecules & R
 
Fingerprinting Chemical Structures
Fingerprinting Chemical StructuresFingerprinting Chemical Structures
Fingerprinting Chemical Structures
 
Exploring Compound Combinations in High Throughput Settings: Going Beyond 1D...
Exploring Compound Combinations in High Throughput Settings: Going Beyond 1D...Exploring Compound Combinations in High Throughput Settings: Going Beyond 1D...
Exploring Compound Combinations in High Throughput Settings: Going Beyond 1D...
 
When the whole is better than the parts
When the whole is better than the partsWhen the whole is better than the parts
When the whole is better than the parts
 
Exploring Compound Combinations in High Throughput Settings: Going Beyond 1D ...
Exploring Compound Combinations in High Throughput Settings: Going Beyond 1D ...Exploring Compound Combinations in High Throughput Settings: Going Beyond 1D ...
Exploring Compound Combinations in High Throughput Settings: Going Beyond 1D ...
 
Pushing Chemical Biology Through the Pipes
Pushing Chemical Biology Through the PipesPushing Chemical Biology Through the Pipes
Pushing Chemical Biology Through the Pipes
 
Characterization and visualization of compound combination responses in a hig...
Characterization and visualization of compound combination responses in a hig...Characterization and visualization of compound combination responses in a hig...
Characterization and visualization of compound combination responses in a hig...
 
The BioAssay Research Database
The BioAssay Research DatabaseThe BioAssay Research Database
The BioAssay Research Database
 
Cloudy with a Touch of Cheminformatics
Cloudy with a Touch of CheminformaticsCloudy with a Touch of Cheminformatics
Cloudy with a Touch of Cheminformatics
 
Chemical Data Mining: Open Source & Reproducible
Chemical Data Mining: Open Source & ReproducibleChemical Data Mining: Open Source & Reproducible
Chemical Data Mining: Open Source & Reproducible
 
Chemogenomics in the cloud: Is the sky the limit?
Chemogenomics in the cloud: Is the sky the limit?Chemogenomics in the cloud: Is the sky the limit?
Chemogenomics in the cloud: Is the sky the limit?
 
Quantifying Text Sentiment in R
Quantifying Text Sentiment in RQuantifying Text Sentiment in R
Quantifying Text Sentiment in R
 
PMML for QSAR Model Exchange
PMML for QSAR Model Exchange PMML for QSAR Model Exchange
PMML for QSAR Model Exchange
 
Smashing Molecules
Smashing MoleculesSmashing Molecules
Smashing Molecules
 

Último

PSP3 employability assessment form .docx
PSP3 employability assessment form .docxPSP3 employability assessment form .docx
PSP3 employability assessment form .docxmarwaahmad357
 
IB Biology New syllabus B3.2 Transport.pptx
IB Biology New syllabus B3.2 Transport.pptxIB Biology New syllabus B3.2 Transport.pptx
IB Biology New syllabus B3.2 Transport.pptxUalikhanKalkhojayev1
 
Pests of ragi_Identification, Binomics_Dr.UPR
Pests of ragi_Identification, Binomics_Dr.UPRPests of ragi_Identification, Binomics_Dr.UPR
Pests of ragi_Identification, Binomics_Dr.UPRPirithiRaju
 
3.2 Pests of Sorghum_Identification, Symptoms and nature of damage, Binomics,...
3.2 Pests of Sorghum_Identification, Symptoms and nature of damage, Binomics,...3.2 Pests of Sorghum_Identification, Symptoms and nature of damage, Binomics,...
3.2 Pests of Sorghum_Identification, Symptoms and nature of damage, Binomics,...PirithiRaju
 
Pests of wheat_Identification, Bionomics, Damage symptoms, IPM_Dr.UPR.pdf
Pests of wheat_Identification, Bionomics, Damage symptoms, IPM_Dr.UPR.pdfPests of wheat_Identification, Bionomics, Damage symptoms, IPM_Dr.UPR.pdf
Pests of wheat_Identification, Bionomics, Damage symptoms, IPM_Dr.UPR.pdfPirithiRaju
 
Exploration Method’s in Archaeological Studies & Research
Exploration Method’s in Archaeological Studies & ResearchExploration Method’s in Archaeological Studies & Research
Exploration Method’s in Archaeological Studies & ResearchPrachya Adhyayan
 
Role of Herbs in Cosmetics in Cosmetic Science.
Role of Herbs in Cosmetics in Cosmetic Science.Role of Herbs in Cosmetics in Cosmetic Science.
Role of Herbs in Cosmetics in Cosmetic Science.ShwetaHattimare
 
Gender board diversity spillovers and the public eye
Gender board diversity spillovers and the public eyeGender board diversity spillovers and the public eye
Gender board diversity spillovers and the public eyeGRAPE
 
Gene transfer in plants agrobacterium.pdf
Gene transfer in plants agrobacterium.pdfGene transfer in plants agrobacterium.pdf
Gene transfer in plants agrobacterium.pdfNetHelix
 
geometric quantization on coadjoint orbits
geometric quantization on coadjoint orbitsgeometric quantization on coadjoint orbits
geometric quantization on coadjoint orbitsHassan Jolany
 
soft skills question paper set for bba ca
soft skills question paper set for bba casoft skills question paper set for bba ca
soft skills question paper set for bba caohsadfeeling
 
Human brain.. It's parts and function.
Human brain.. It's parts and function. Human brain.. It's parts and function.
Human brain.. It's parts and function. MUKTA MANJARI SAHOO
 
M.Pharm - Question Bank - Drug Delivery Systems
M.Pharm - Question Bank - Drug Delivery SystemsM.Pharm - Question Bank - Drug Delivery Systems
M.Pharm - Question Bank - Drug Delivery SystemsSumathi Arumugam
 
SCIENCE 6 QUARTER 3 REVIEWER(FRICTION, GRAVITY, ENERGY AND SPEED).pptx
SCIENCE 6 QUARTER 3 REVIEWER(FRICTION, GRAVITY, ENERGY AND SPEED).pptxSCIENCE 6 QUARTER 3 REVIEWER(FRICTION, GRAVITY, ENERGY AND SPEED).pptx
SCIENCE 6 QUARTER 3 REVIEWER(FRICTION, GRAVITY, ENERGY AND SPEED).pptxROVELYNEDELUNA3
 
Intensive Housing systems for Poultry.pptx
Intensive Housing systems for Poultry.pptxIntensive Housing systems for Poultry.pptx
Intensive Housing systems for Poultry.pptxHarshiniAlapati
 
THE HISTOLOGY OF THE CARDIOVASCULAR SYSTEM 2024.pptx
THE HISTOLOGY OF THE CARDIOVASCULAR SYSTEM 2024.pptxTHE HISTOLOGY OF THE CARDIOVASCULAR SYSTEM 2024.pptx
THE HISTOLOGY OF THE CARDIOVASCULAR SYSTEM 2024.pptxAkinrotimiOluwadunsi
 
Contracts with Interdependent Preferences (2)
Contracts with Interdependent Preferences (2)Contracts with Interdependent Preferences (2)
Contracts with Interdependent Preferences (2)GRAPE
 
An intro to explainable AI for polar climate science
An intro to  explainable AI for  polar climate scienceAn intro to  explainable AI for  polar climate science
An intro to explainable AI for polar climate scienceZachary Labe
 
Legacy Analysis of Dark Matter Annihilation from the Milky Way Dwarf Spheroid...
Legacy Analysis of Dark Matter Annihilation from the Milky Way Dwarf Spheroid...Legacy Analysis of Dark Matter Annihilation from the Milky Way Dwarf Spheroid...
Legacy Analysis of Dark Matter Annihilation from the Milky Way Dwarf Spheroid...Sérgio Sacani
 
Physics Serway Jewett 6th edition for Scientists and Engineers
Physics Serway Jewett 6th edition for Scientists and EngineersPhysics Serway Jewett 6th edition for Scientists and Engineers
Physics Serway Jewett 6th edition for Scientists and EngineersAndreaLucarelli
 

Último (20)

PSP3 employability assessment form .docx
PSP3 employability assessment form .docxPSP3 employability assessment form .docx
PSP3 employability assessment form .docx
 
IB Biology New syllabus B3.2 Transport.pptx
IB Biology New syllabus B3.2 Transport.pptxIB Biology New syllabus B3.2 Transport.pptx
IB Biology New syllabus B3.2 Transport.pptx
 
Pests of ragi_Identification, Binomics_Dr.UPR
Pests of ragi_Identification, Binomics_Dr.UPRPests of ragi_Identification, Binomics_Dr.UPR
Pests of ragi_Identification, Binomics_Dr.UPR
 
3.2 Pests of Sorghum_Identification, Symptoms and nature of damage, Binomics,...
3.2 Pests of Sorghum_Identification, Symptoms and nature of damage, Binomics,...3.2 Pests of Sorghum_Identification, Symptoms and nature of damage, Binomics,...
3.2 Pests of Sorghum_Identification, Symptoms and nature of damage, Binomics,...
 
Pests of wheat_Identification, Bionomics, Damage symptoms, IPM_Dr.UPR.pdf
Pests of wheat_Identification, Bionomics, Damage symptoms, IPM_Dr.UPR.pdfPests of wheat_Identification, Bionomics, Damage symptoms, IPM_Dr.UPR.pdf
Pests of wheat_Identification, Bionomics, Damage symptoms, IPM_Dr.UPR.pdf
 
Exploration Method’s in Archaeological Studies & Research
Exploration Method’s in Archaeological Studies & ResearchExploration Method’s in Archaeological Studies & Research
Exploration Method’s in Archaeological Studies & Research
 
Role of Herbs in Cosmetics in Cosmetic Science.
Role of Herbs in Cosmetics in Cosmetic Science.Role of Herbs in Cosmetics in Cosmetic Science.
Role of Herbs in Cosmetics in Cosmetic Science.
 
Gender board diversity spillovers and the public eye
Gender board diversity spillovers and the public eyeGender board diversity spillovers and the public eye
Gender board diversity spillovers and the public eye
 
Gene transfer in plants agrobacterium.pdf
Gene transfer in plants agrobacterium.pdfGene transfer in plants agrobacterium.pdf
Gene transfer in plants agrobacterium.pdf
 
geometric quantization on coadjoint orbits
geometric quantization on coadjoint orbitsgeometric quantization on coadjoint orbits
geometric quantization on coadjoint orbits
 
soft skills question paper set for bba ca
soft skills question paper set for bba casoft skills question paper set for bba ca
soft skills question paper set for bba ca
 
Human brain.. It's parts and function.
Human brain.. It's parts and function. Human brain.. It's parts and function.
Human brain.. It's parts and function.
 
M.Pharm - Question Bank - Drug Delivery Systems
M.Pharm - Question Bank - Drug Delivery SystemsM.Pharm - Question Bank - Drug Delivery Systems
M.Pharm - Question Bank - Drug Delivery Systems
 
SCIENCE 6 QUARTER 3 REVIEWER(FRICTION, GRAVITY, ENERGY AND SPEED).pptx
SCIENCE 6 QUARTER 3 REVIEWER(FRICTION, GRAVITY, ENERGY AND SPEED).pptxSCIENCE 6 QUARTER 3 REVIEWER(FRICTION, GRAVITY, ENERGY AND SPEED).pptx
SCIENCE 6 QUARTER 3 REVIEWER(FRICTION, GRAVITY, ENERGY AND SPEED).pptx
 
Intensive Housing systems for Poultry.pptx
Intensive Housing systems for Poultry.pptxIntensive Housing systems for Poultry.pptx
Intensive Housing systems for Poultry.pptx
 
THE HISTOLOGY OF THE CARDIOVASCULAR SYSTEM 2024.pptx
THE HISTOLOGY OF THE CARDIOVASCULAR SYSTEM 2024.pptxTHE HISTOLOGY OF THE CARDIOVASCULAR SYSTEM 2024.pptx
THE HISTOLOGY OF THE CARDIOVASCULAR SYSTEM 2024.pptx
 
Contracts with Interdependent Preferences (2)
Contracts with Interdependent Preferences (2)Contracts with Interdependent Preferences (2)
Contracts with Interdependent Preferences (2)
 
An intro to explainable AI for polar climate science
An intro to  explainable AI for  polar climate scienceAn intro to  explainable AI for  polar climate science
An intro to explainable AI for polar climate science
 
Legacy Analysis of Dark Matter Annihilation from the Milky Way Dwarf Spheroid...
Legacy Analysis of Dark Matter Annihilation from the Milky Way Dwarf Spheroid...Legacy Analysis of Dark Matter Annihilation from the Milky Way Dwarf Spheroid...
Legacy Analysis of Dark Matter Annihilation from the Milky Way Dwarf Spheroid...
 
Physics Serway Jewett 6th edition for Scientists and Engineers
Physics Serway Jewett 6th edition for Scientists and EngineersPhysics Serway Jewett 6th edition for Scientists and Engineers
Physics Serway Jewett 6th edition for Scientists and Engineers
 

Pharos – A Torch to Use in Your Journey In the Dark Genome