1. Workflows
for
biological
research
at
Notre
Dame
Sandra
Gesing
sandra.gesing@nd.edu

2. Biological
Research
at
Notre
Dame
• genomics
• proteomics
• molecular
simula0ons
• docking
• disease
modeling
Black
Swallowtail
-­‐
larvae
and
bu9erfly

3. Molecular
Simula@ons
and
Docking
• Predic0on
and
analysis
of
molecular
structures
• Numerous
applica0ons,
e.g.
– Materials
science
– Drug
design
ligands
target
docking
?

4. Molecular
Simula@ons
and
Docking
• Predic0on
and
analysis
of
molecular
structures
• Numerous
applica0ons,
e.g.
– Materials
science
– Drug
design
ligands
target
docking
binding
energy
scoring
func0ons
binding
pocket

5. Disease
Modeling
• vector-­‐borne
diseases,
e.g.,
lympha0c
filariaris,
malaria
• mathema0cal
models
• predic0on
of
interven0ons
• data
on
weather,
demographics,
interven0ons

6. Biological
Research
at
Notre
Dame
• technologies
and
methods
for
crea0ng,
analyzing
and
predic0on
of
data
available
• immense
amount
of
data,
e.g.,
– ZINC
database:
~20
Mio
molecular
structures
– Human
genome:
~
3
Bio
DNA
base
pairs
• compute-­‐intensive
tasks

7. Workflows
• a
sequence
of
connected
steps
in
a
defined
order
based
on
their
control
and
data
dependencies
12181 acatttctac caacagtgga tgaggttgtt
ggtctatgtt ctcaccaaat ttggtgttgt 12241
cagtctttta aattttaacc tttagagaag agtcatacag
tcaatagcct tttttagctt 12301 gaccatccta
atagatacac agtggtgtct cactgtgatt ttaatttgca
ttttcctgct 12361 gactaattat gttgagcttg
ttaccattta gacaacttca ttagagaag atagaatcaa
Figure
copied
from:
Stuart
Owen
„Workflows
with
Taverna“

8. Communi@es
• users
are
generally
not
IT
specialists

9. MoSGrid
Molecular
Simula0on
Grid
• science
gateway
integrated
with
underlying
compute
and
data
management
infrastructure
• distributed
workflow
management
• data
repository

10. MoSGrid

11. MoSGrid

12. MoSGrid
–
Applica@on
Areas
Molecular
Dynamics
• Study
and
simula0on
of
molecular
mo0on
Quantum
Chemistry
• Study
and
simula0on
of
molecular
electronic
behavior
rela0ve
to
their
chemical
reac0vity
Docking
• Main
focus
on
evalua0on
of
ligand-­‐receptor
interac0ons
(e.g.,
for
drug
design)

13. MoSGrid

14. MoSGrid

15. MoSGrid

16. VectorBase

17. VectorBase

18. VectorBase
-­‐
Galaxy

19. VectorBase
-­‐
Galaxy

20. Disease
Modeling
–
Baysian
Model

21. Disease
Modeling
–
Baysian
Model

22. An
Old
Idea:
Makefiles
part1 part2 part3: input.data split.py
./split.py input.data
out1: part1 mysim.exe
./mysim.exe part1 >out1
out2: part2 mysim.exe
./mysim.exe part2 >out2
out3: part3 mysim.exe
./mysim.exe part3 >out3
result: out1 out2 out3 join.py
./join.py out1 out2 out3 > result
Slide
copied
from:
Douglas
Thain
„Toward
a
Common
Model
for
Highly
Concurrent
Applica0ons“

23. Makeflow
=
Make
+
Workflow
Makeflow
Local
Condor
SGE
Work
Queue
• Provides
portability
across
batch
systems.
• Enable
parallelism
(but
not
too
much!)
• Fault
tolerance
at
mul0ple
scales.
• Data
and
resource
management.
Slide
copied
from:
Douglas
Thain
„Toward
a
Common
Model
for
Highly
Concurrent
Applica0ons“

24. Outlook
• crea0on
of
more
workflows
in
science
gateways
• integra0on
of
science
gateways
with
ICTBioMed
infrastructure
• integra0on
of
Makeflow
and
ICTBioMed
infrastructure

25. PARTNERS