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BIMSB	Bioinforma-cs	Pla2orm	
Overview	
Altuna	Akalin	
@AltunaAkalin	
BIOINFORMATICS PLATFORM
Bioinforma-cs	Pla2orm	at	MDC/
BIMSB	
-	Gene	regula-on	
-	Comp.	(Epi)genomics:	disease	and	development	
Data-intensive	computa-onal	methods		
to	infer	biological	knowledge	
Research	
Collabora-on	
Training	
Scien-fic	IT	
Support	
BIOINFORMATICS
PLATFORM
-Maintain	databases	
- Maintain	scien-fic	soNware	
	
hOp://bioinforma-cs.mdc-berlin.de
Scien-fic	IT	support
MDC	Hubs	and	UCSC	Genome	browser	
hOp://genome.mdc-berlin.de	
hOps://bimsbsta-c.mdc-berlin.net/
Scien-fic	SoNware	Support	
hOp://guix.mdc-berlin.de	
	
Tired	of	trying	to	
install	soNware?	
	
Can’t	demul-plex?	
	
Try	GNU	Guix
Galaxy	@	BIMSB	
•  “Galaxy	is	an	open	web-based	pla2orm	for	data-intensive	
biomedical	research”	(only	available	within	campus)	
hOp://galaxy.mdc-berlin.net
Databases	and	Virtual	Machines	
•  BIMSB	databases	and	virtual	machines	that	
host	the	web	apps	and	databases	are	
maintained	by	BIMSB	sys.	admins.
Training	
•  Pla2orm	provides	training	for	development	of	
bioinforma-cs	skills	
•  ~10	courses/tutorials	un-l	now	
– R,	computa-onal	genomics,	galaxy	and	unix	
related	courses	
•  Yearly	computa-onal	genomics	course	open	
to	external	applicants
Public	trainings/workshops	
More	info	hOp://bioinforma-cs.mdc-berlin.de/training.html
Learning	material	produced	by	the	
pla2orm	
•  Computa-onal		genomics	material	
– Includes	introductory	material	for	computa-onal	
genomics	and	hands-on	data	analysis	
– hOp://compgenomr.github.io/book	
•  Unix	+	SGE	material	
– Includes	basic	Unix	and	SGE	commands	needed	to	
get	started	on	a	Unix+SGE	environment	
– hOp://bioinforma-cs.mdc-berlin.de/
intro2UnixSGE
BIMSB	Bioinforma-cs	walk-in	clinics	
Collabora-on	No	ac-on	Referral	Consulta-on	
Advise	you	how	to	
proceed	with	your	
data	analysis	
Walk-in	clinic	outcome	
Refer	you	to	a	group	
more	experienced	in	
that	par-cular	
problem	
Some-mes	there	is	
nothing	to	be	done	
~	monthly	event	dedicated	to	providing	consulta-on	for	bioinforma-cs	problems
Collabora-on
Main	collabora-on	structures	
•  Small	scale	
–  Running	workflows	we	established	outpudng	predefined	
reports	(currently:	RNA-seq,	BS-seq,	ChIP-seq,	SNP/CNV	calling)	
–  Sta-s-cal	modeling	with	already	processed	data	
–  Depends	on:	
•  	available	man-hours	
•  Large	scale		
–  Needs	integra-on	and	analysis	of	large	number	of	samples	
–  Needs	development	of	new	workflows	
–  Depends	on:	
•  Overlap	with	pla2orm	research	objec-ves	
•  Available	man-hours	
•  In	all	cases,	authorship	status	must	be	discussed	in	
advance.
More	info	at…	
hOp://bioinforma-cs.mdc-berlin.de

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