Author Archives: user

Farnam disk usage

total 5.3132E+11 of 600 TB
gg487 79451212160
sl857 45798747392
jx98 40506299392
fn64 37325542016
tg397 36359539072
mg888 31966766720
jz435 28411651328
sk972 21944677120
pse5 20345500672
sl2373 15416565888
dl598 15304713216
cs784 13925904256
cy288 11872786432
mr724 11768326784
sl847 9957541888
wum2 9319828736
ll426 8905029760
pmm49 8177639424
jad248 7989755008
yy222 6347266176
rrk24 6182451584
yf9 5816445952
hm444 5719293952
mihali 5459016704
yy532 4658633728
lc848 4090249984
meg98 3993349632
ah633 3367398912
bp272 2906803456
xk4 2393895168
jjl86 2074232704
rdb9 1763952640
msp48 1748680320
as2665 1596345472
ky26 1583088768
ml724 1557992448
jl56 1480538368
ha275 1467031936
jw2394 1423484800
sb238 1275168128
gf3 1189340928
jrb97 1012897664
slw67 824147840
pdm32 771726720
lh372 671649152
jsr59 592016256
as898 506352512
xc279 434491136
dc547 427202432
mpw6 385383040
hz244 374372096
km735 337744640
nb23 324053504
ls926 314810880
keckadmins 265108480
aa544 249558400
zc264 244803200
xl348 237337088
simen 163574272
xz374 162198144
lr579 159751424
yf95 152837120
nmb38 115795456
jjl83 109213440
mas343 96425216
yk336 95688832
williams 95688832
zl222 68034176
wb244 63682432
rka24 59127808
yy448 46536704
aa65 44632832
gene760 33406080
mx55 27679616
zhao 25241600
shuch 22284288
amg89 21919360
co254 21889920
an377 19965312
xm24 19335680
jc2296 17970560
jw72 17455616
njc2 16694016
ajf73 10993024
root 9156608
jk935 6167936
law72 4700416
cc59 4636672
yz464 1122176
gene760_2016 475520
bab99 387584
tl444 326144
dr395 185472
jhq4 117760
mj332 60160
rm658 4096
jjp76 3968

SPECIAL ANNOUNCEMENT FROM THE NHGRI DIRECTOR

https://grants.nih.gov/grants/guide/notice-files/NOT-OD-18-134.html

In order to capitalize on the opportunities presented by advances in data science, the National Institutes of Health (NIH) is developing a Strategic Plan for Data Science. This plan describes NIH’s
overarching goals, strategic objectives, and implementation tactics for promoting the modernization of the NIH-funded biomedical data science ecosystem. As part of the planning process, NIH has published a Request for Information (RFI) to seek input from stakeholders, including members of the scientific community, academic institutions, the private sector, health professionals, professional societies, advocacy groups, patient communities, as well as other interested members of the public.

farnam disk usage

total 5.1925E+11 of 600TB
gg487 79014179456
sl857 45684084864
jx98 40477220224
fn64 37359098752
tg397 36344327680
mg888 31897883264
jz435 28383941120
sk972 21924789376
pse5 20335859200
sl2373 15416500352
dl598 15304710912
cs784 13924463744
mr724 11768326784
sl847 9951345920
wum2 9001203328
ll426 8905029760
pmm49 8177639424
jad248 7989755008
yy222 6347266176
rrk24 6182451584
yf9 5816445952
hm444 5719293952
mihali 5459016704
lc848 4090249984
meg98 3984629504
ah633 3367398912
yy532 3286718592
bp272 2906803456
cy288 2414961152
xk4 2412787072
jjl86 2058988544
rdb9 1763952640
msp48 1748680320
as2665 1596345472
ky26 1583088768
ml724 1557992448
jl56 1480538368
ha275 1467031936
jw2394 1423484800
sb238 1275168128
gf3 1189340928
jrb97 1012897664
slw67 816497408
pdm32 752482048
lh372 671649152
jsr59 592016256
as898 506352512
xc279 434235264
dc547 427202048
mpw6 385383040
hz244 374372096
km735 337744640
nb23 324053504
ls926 314810880
keckadmins 265108480
aa544 249558400
xl348 237337088
simen 163574272
xz374 162198144
lr579 159751424
yf95 152253312
nmb38 115795456
jjl83 109213440
mas343 96425216
yk336 95688832
williams 95688832
zl222 68034176
wb244 63682432
rka24 59127808
yy448 46536704
aa65 44632832
zc264 43432832
gene760 33406080
mx55 27679616
zhao 25241600
amg89 21919360
co254 21889920
an377 19965312
xm24 19335680
jc2296 17970560
jw72 17455616
njc2 16694016
root 9156608
jk935 6167936
law72 4700416
cc59 4636672
shuch 3039616
yz464 1122176
gene760_2016 475520
bab99 387584
tl444 326144
dr395 185472
jhq4 117760
mj332 60160
rm658 4096
jjp76 3968

Mbbfacultyall FW from Chemistry Dept.: Organic Chemistry Seminar – Daniel Kahne – 3/6/18

On Tuesday, March 6, 2018, Professor Daniel Kahne of Harvard University will be presenting The 2018 Treat B. Johnson Lecture in Organic Chemistry.

The title of his talk is “Molecular Machines That Build Membranes”.

You are welcomed to attend the lecture which will be held at The Sterling Chemistry Lab – 225 Prospect Street – in SCL 110.

If you cannot attend, you can watch by going to the following link:

https://yale.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=848c083b-b7cc-4b48-93ed-a897010fbd2e
KAHNE Poster.pdf

NIMH Virtual Workshop on Quantum Computing

NIMH VIRTUAL WORKSHOP:

SOLVING COMPUTATIONAL CHALLENGES IN GENOMICS AND NEUROSCIENCE VIA PARALLEL & QUANTUM COMPUTING

March 28, 2018

9:00 am – 1:00 pm EST

Goal of the workshop

This virtual workshop aims to highlight core computational problems faced by genetics and the subdomains of neuroscience that parallel or quantum computing can address. By bringing together experts in quantum and parallel computing with experts in genetics and neuroscience, we hope to start a dialogue between academic and industry partners working in this area with the focus on algorithm optimization and development. This virtual workshop will be the forum and the nexus to find convergence between cross-disciplinary fields that are operating mostly independently – 1) genomics and neuroscience, and 2) AI/machine learning and 3) quantum computing. The goal is to identify key avenues for computation optimization via parallel and quantum algorithms. This workshop will facilitate the use of state-of-art computational technologies for addressing core bottlenecks in genomics and neuroscience.

Overview

This workshop will cover the following topics with 5 minutes break following each topic discussion:

  • Opening Remarks (10 min)
  • Topic 1: Computational Challenges in Genetics and Neuroscience (1.5 hour)
  • Topic 2: AI, machine learning and parallel computing (45 min)
  • Topic 3: Quantum Algorithms for Accelerated Computation: Opportunities and Challenges (1 hour)
  • Roundtable Discussion & Summary (30 mins)

*NOTE: Some speakers are yet to be confirmed and/or subject to change.

9:00 – 9:10 am:Opening Remarks – Thomas Lehner, Geetha Senthil, Susan

Wright, National Institute of Mental Health, Office of Genomics Research Coordination

Morning Session

Chairs: Alan Anticevic, Ph.D., Yale University and Alan Aspuru-Guzik, Ph.D., Harvard University

Topic 1: Computational Challenges in Genetics and Neuroscience

This session is to highlight where computational challenges/bottlenecks exist at the level of scaling (data and computational features) and computational speedup.

9:10 – 9:25 am: Presentation 1: Genetics and functional genomics

Michael McConnell, Ph.D., University of Virginia, Michael Gandal, M.D., Ph.D., University of California, Los Angeles

9:25 – 9:40 am: Presentation 2: Neurophysiology (processing data, extracting, analysis)

Potential speakers: Mike Halassa, M.D., Ph.D., Massachusetts Institute of Technology

9:40 – 9:55 am: Presentation 3: Neuroimaging

Potential speakers: Alan Anticevic, Ph.D., Yale University, Stephen Smith, Oxford

9:55 – 10:10 am: Presentation 4: Quantitative deep phenotypic analysis

Potential speakers: Andrey Rzhetsky, Ph.D., University of Chicago, Justin Baker, M.D., Ph.D., Massachusetts General Hospital, Jukka-Pekka Onnela, M.Sc., Ph.D., Harvard University

10:10 – 10:25 am: Presentation 5: Computational modeling

Suggested topic: Spiking and neural models and ion channel modelling – spiking network simulation

Speakers: John Murray, Ph.D., Yale University, Michael Hines, Ph.D., Yale University

10:25 – 10:30 am: Break

Topic 2: AI, machine deep learning and parallel computing

This session is to discuss application of state-of-the-art classical parallel computing algorithm applications for machine learning, simulation, & optimization of analysis with ‘big’ data.

10:30 – 10:45 am: Presentation 1: Overview of machine learning via classical and parallel computing technologies

Potential speakers: Guillermo Sapiro, M.Sc., Ph.D., Duke University

10:45 – 11:00 am: Presentation 2: Deep Learning for AI applications – e.g. DeepMind

Potential speakers: Tim Lillicrap, Ph.D., DeepMind

11:00 – 11:15 am: Presentation 3: Parallel processing & GPUs

Suggested topic: Nvidia parallel processing & GPU capabilities for efficient high-performance applications

Potential speakers: Alan will reach out to his contact at Nvidia

11:15 – 11:20 am: Break

Afternoon Session:

Chairs: Aram Harrow, Ph.D., Massachusetts Institute of Technology, and John Murray, Ph.D.,

Yale University

Topic 3: Quantum Algorithms for Accelerated Computation: Opportunities and Challenges

This session will discuss the current state of quantum hardware and algorithms. What kind of advantages (either in terms of speed or solution quality) can be obtained by using quantum machine learning? How close are existing or proposed near-term hardware platforms to being able to implement these algorithms?

11:20 – 11:35 am: Presentation 1: Overview and primer: what is quantum computing good for?

Potential speakers: Alán Aspuru-Guzik, Ph.D., Harvard University

11:35 – 11:50 am: Presentation 2: Status and Prospects for Quantum Hardware

Potential speaker: Nicole Barberis, IBM

11:50 am – 12:05 pm: Presentation 3: Promising Quantum Computing Algorithms on the

Horizon

Potential speakers: Ashley Montanaro, Ph.D., University of Bristol

12:05 – 12:20 pm: Presentation 4: Quantum Machine Learning and Optimization

Seth Lloyd, Massachusetts Institute of Technology

12:20 – 12:30 pm: Break

12:30 – 12:50 pm: Roundtable Discussion & Summary

Moderators: Stefan Bekiranov, University of Virginia & John Murray, Yale University

  • What are the immediate avenues for computation optimization via parallel computing?
  • Which problems are suitable for parallel vs. quantum computing?
  • What are the distinct challenges facing parallel vs quantum computing platforms?
  • Which are the most impactful avenues for quantum algorithm development from the standpoint of neuroscience and genomics?
  • Opportunities for public private partnership?

    12:50 – 1:00 pm: Summary/Closing Remarks

    Potential speakers: Alán Aspuru-Guzik, Harvard University, Alan Anticevic, Yale University

    1:00 pm: Adjourn

NIMH Quantum Computing Virtual Workshop Agenda_02-15-2018.docx