Thank you, Mark! Yes, this will be a great topic for the audience. Look forward to meeting you next month. Feel free to email or contact me should you need any further help. My cell phone is 317.622.8881.
Jake
-----Original Message-----
From: Mark Gerstein <mark@gersteinlab.org>
Sent: Thursday, February 14, 2019 7:07 PM
To: Chen, Jake Y <jakechen@uab.edu>
Cc: glabstracts.mbglab@blogger.com
Subject: Abstract for keynote talk at MCBIOS '19, Birmingham, AL Mar 28-30th (* i0mcbios *)
Talk Title:
Brain Genomics
Abstract:
Despite progress in defining genetic risk for psychiatric disorders, their molecular mechanisms remain elusive. Addressing this, the PsychENCODE Consortium has generated a comprehensive online resource for the adult brain across 1866 individuals. The PsychENCODE resource contains ~79,000 brain-active enhancers, sets of Hi-C linkages, and topologically associating domains; single-cell expression profiles for many cell types; expression quantitative-trait loci (QTLs); and further QTLs associated with chromatin, splicing, and cell-type proportions. Integration shows that varying cell-type proportions largely account for the cross-population variation in expression (with
>88% reconstruction accuracy). It also allows the building of a gene
regulatory network, linking genome-wide association study variants to genes (e.g., 321 for schizophrenia). We embed this network into an interpretable deep-learning model, which improves disease prediction by ~6-fold versus polygenic risk scores and identifies key genes and pathways in psychiatric disorders.
URL:
resource.psychencode.org
Thursday, February 14, 2019
Abstract for keynote talk at MCBIOS '19, Birmingham, AL Mar 28-30th (* i0mcbios *)
Talk Title:
Brain Genomics
Abstract:
Despite progress in defining genetic risk for psychiatric disorders,
their molecular mechanisms remain elusive. Addressing this, the
PsychENCODE Consortium has generated a comprehensive online resource
for the adult brain across 1866 individuals. The PsychENCODE resource
contains ~79,000 brain-active enhancers, sets of Hi-C linkages, and
topologically associating domains; single-cell expression profiles for
many cell types; expression quantitative-trait loci (QTLs); and
further QTLs associated with chromatin, splicing, and cell-type
proportions. Integration shows that varying cell-type proportions
largely account for the cross-population variation in expression (with
>88% reconstruction accuracy). It also allows the building of a gene
regulatory network, linking genome-wide association study variants to
genes (e.g., 321 for schizophrenia). We embed this network into an
interpretable deep-learning model, which improves disease prediction
by ~6-fold versus polygenic risk scores and identifies key genes and
pathways in psychiatric disorders.
URL:
resource.psychencode.org
Brain Genomics
Abstract:
Despite progress in defining genetic risk for psychiatric disorders,
their molecular mechanisms remain elusive. Addressing this, the
PsychENCODE Consortium has generated a comprehensive online resource
for the adult brain across 1866 individuals. The PsychENCODE resource
contains ~79,000 brain-active enhancers, sets of Hi-C linkages, and
topologically associating domains; single-cell expression profiles for
many cell types; expression quantitative-trait loci (QTLs); and
further QTLs associated with chromatin, splicing, and cell-type
proportions. Integration shows that varying cell-type proportions
largely account for the cross-population variation in expression (with
>88% reconstruction accuracy). It also allows the building of a gene
regulatory network, linking genome-wide association study variants to
genes (e.g., 321 for schizophrenia). We embed this network into an
interpretable deep-learning model, which improves disease prediction
by ~6-fold versus polygenic risk scores and identifies key genes and
pathways in psychiatric disorders.
URL:
resource.psychencode.org
Saturday, October 27, 2018
Fwd: Request for Information and Travel to the Sigma Xi Annual Meeting
BIG DATA AND THE FUTURE OF RESEARCH SYMPOSIA
October 26–28, 2018
Hyatt Regency San Francisco Airport, California
#SigmaXimtg
https://www.sigmaxi.org/meetings-events/annual-meeting-and-student-research-conference/big-data-symposia
Posted & "tweeted" my talk, viz:
https://twitter.com/MarkGerstein/status/1055636248956690432
(I'd use the ppt.)
Talk title and abstract
"Personal Genomics & Data Science"
In this seminar, I will discuss issues in transcriptome analysis. I
will first talk about some core aspects - how we analyze the activity
patterns of genes in human disease. In particular, I will focus on
disorders of the brain, which affect nearly a fifth of the world's
population. Robust phenotype-genotype associations have been
established for a number of brain disorders including psychiatric
diseases (e.g., schizophrenia, bipolar disorder). However,
understanding the molecular causes of brain disorders is still a
challenge. To address this, the PsychENCODE consortium generated
thousands of transcriptome (bulk and single-cell) datasets from 1,866
individuals. Using these data, we have developed a set of
interpretable machine learning approaches for deciphering functional
genomic elements and linkages in the brain and psychiatric disorders.
In particular, we deconvolved the bulk tissue expression across
individuals using single-cell data via non-negative matrix
factorization and non-negative least squares and found that
differences in the proportions of cell types explain >85% of the
cross-population variation observed. Additionally, we developed an
interpretable deep-learning model embedding the physical regulatory
network to predict phenotype from genotype. Our model uses a
conditional Deep Boltzmann Machine architecture and introduces lateral
connectivity at the visible layer to embed the biological structure
learned from the regulatory network and QTL linkages. Our model
improves disease prediction (by 6-fold compared to additive polygenic
risk scores), highlights key genes for disorders, and allows
imputation of missing transcriptome information from genotype data
alone. In the second half of the talk, I will look at the "data
exhaust" from transcriptome analysis - that is, how one can find
additional things from this data than what is necessarily intended.
First, I will focus on genomic privacy: How looking at the
quantifications of expression levels can potentially reveal something
about the subjects studied, and how one can take steps to protect
patient anonymity. Next, I will look at how the social activity of
researchers generating transcriptome datasets in itself creates
revealing patterns in the scientific literature.
==
i0sigma
October 26–28, 2018
Hyatt Regency San Francisco Airport, California
#SigmaXimtg
https://www.sigmaxi.org/meetings-events/annual-meeting-and-student-research-conference/big-data-symposia
Posted & "tweeted" my talk, viz:
https://twitter.com/MarkGerstein/status/1055636248956690432
(I'd use the ppt.)
Talk title and abstract
"Personal Genomics & Data Science"
In this seminar, I will discuss issues in transcriptome analysis. I
will first talk about some core aspects - how we analyze the activity
patterns of genes in human disease. In particular, I will focus on
disorders of the brain, which affect nearly a fifth of the world's
population. Robust phenotype-genotype associations have been
established for a number of brain disorders including psychiatric
diseases (e.g., schizophrenia, bipolar disorder). However,
understanding the molecular causes of brain disorders is still a
challenge. To address this, the PsychENCODE consortium generated
thousands of transcriptome (bulk and single-cell) datasets from 1,866
individuals. Using these data, we have developed a set of
interpretable machine learning approaches for deciphering functional
genomic elements and linkages in the brain and psychiatric disorders.
In particular, we deconvolved the bulk tissue expression across
individuals using single-cell data via non-negative matrix
factorization and non-negative least squares and found that
differences in the proportions of cell types explain >85% of the
cross-population variation observed. Additionally, we developed an
interpretable deep-learning model embedding the physical regulatory
network to predict phenotype from genotype. Our model uses a
conditional Deep Boltzmann Machine architecture and introduces lateral
connectivity at the visible layer to embed the biological structure
learned from the regulatory network and QTL linkages. Our model
improves disease prediction (by 6-fold compared to additive polygenic
risk scores), highlights key genes for disorders, and allows
imputation of missing transcriptome information from genotype data
alone. In the second half of the talk, I will look at the "data
exhaust" from transcriptome analysis - that is, how one can find
additional things from this data than what is necessarily intended.
First, I will focus on genomic privacy: How looking at the
quantifications of expression levels can potentially reveal something
about the subjects studied, and how one can take steps to protect
patient anonymity. Next, I will look at how the social activity of
researchers generating transcriptome datasets in itself creates
revealing patterns in the scientific literature.
==
i0sigma
Monday, July 16, 2018
Re: Donation
Hello
I am Mrs. Sigrid Rausing, a Swedish business tycoon, investor, and philanthropist. Who distributed approximately 208.3 million Dollars to human rights organizations charity globally, and I also pledged to give away the rest of 25% this year 2018. However, your E-mail which was randomly selected by Google Inc. as an active web user to receive a donation of One Million Dollars as part of Sigrid Rausing charity project. Kindly Confirm ownership of your E-mail by contacting Sigrid Rausing via email for claim.
You can also read more about Sigrid Rausing via the link https://en.wikipedia.org/wiki/Sigrid_Rausing
Contact me via my E-mail: sigrid.rausing@yandex.com
Sunday, March 18, 2018
Abstract for talk at McGill University, Human Genetics Seminar Series (*i0mcg18*)
Title:
Prioritizing Variants in Personal Genomes, with particular application to cancer
Abstract:
My talk will focus on prioritizing genetic variants associated with
cancer, to identify key variants driving cancer progression. First, I
will look at the overall functional impact of the variants in cancer
genomes, ranking them in terms of impact, for both coding and
non-coding regions. For the coding analysis, we use the ALoFT and
frustration tools, and for the noncoding analysis, we use FunSeq.
Then, I will look at the recurrence of variants within cancer cohorts.
Here we develop two approaches: one parametric (LARVA) and the other
non-parametric (MOAT). These both depend on background
mutation rate, which, in turn, is linked to genomic features such
as replication timing and TADs. I will discuss tools for analyzing these.
Finally, I will put all these methods together
through application to kidney and prostate cancers.
Prioritizing Variants in Personal Genomes, with particular application to cancer
Abstract:
My talk will focus on prioritizing genetic variants associated with
cancer, to identify key variants driving cancer progression. First, I
will look at the overall functional impact of the variants in cancer
genomes, ranking them in terms of impact, for both coding and
non-coding regions. For the coding analysis, we use the ALoFT and
frustration tools, and for the noncoding analysis, we use FunSeq.
Then, I will look at the recurrence of variants within cancer cohorts.
Here we develop two approaches: one parametric (LARVA) and the other
non-parametric (MOAT). These both depend on background
mutation rate, which, in turn, is linked to genomic features such
as replication timing and TADs. I will discuss tools for analyzing these.
Finally, I will put all these methods together
through application to kidney and prostate cancers.
Tuesday, March 6, 2018
Indian Country Books / Native Media Network
Dear Educator / Communicator :
For the past several months Indian Country Books www.indiancountrybooks.com has been morphing into an interactive platform on Facebook and our web www.nativemedianetwork.com platform to produce, publish and distribute cultural and topical programs to our audience that is tethered to their cell phones.
Please take a look at some of the programming that we have posted on Facebook and archives on our platform at www.nativemedianetwork.com/social .
Our editorial policy is simple to show and illustrate the positive side and diversity of being Native.
We have experienced an exponential growth over the past several months, into the millions of views and viewers and look forward to serving Indian Country with high quality content accessible 24/7 on any web enabled device.
Please take a look at our broadcast channel: www.ndn1.com,
Our Archives: www.nativemedianetwork.com/videos-on-demand/
And most of all our catalog of close to 10,000 titles for of and about Native America:
www.indiancountrybooks.com
The sole support for our platform comes from the sale of books, so I would like to encourage you to purchase your books from us. "Rather than the other guys".
Thank you
Harmon Houghton, Director of Programming
Native Media Network
harmon@indiancoutrybooks.com
Your $$$$ support means a lot to produce and publish authentic content
INVESTMENT/BUSINESS PARTNERSHIP.
Hello Friend,
I am Msgr. Nunzio Scarano priest in the vatican city rome italy
Compliment of the day, I got your contact information from a
reputable business/professional directory of your country which gives me
assurance of your legibility as a person. I send you this brief letter to
solicit your partnership to transfer 30 million euro
tranfer to you. i hope this information meet you well as I know you will be curious to know why/how.
You can contact me on my email:
priest Nunzio Scarano
Email: scarano22@163.com
please see the link below:
https://www.nytimes.com/2014/10/19/business/of-virtue-and-vice-and-a-vatican-priest.html
Yours sincerely,
priest Nunzio Scarano
I am Msgr. Nunzio Scarano priest in the vatican city rome italy
Compliment of the day, I got your contact information from a
reputable business/professional directory of your country which gives me
assurance of your legibility as a person. I send you this brief letter to
solicit your partnership to transfer 30 million euro
tranfer to you. i hope this information meet you well as I know you will be curious to know why/how.
You can contact me on my email:
priest Nunzio Scarano
Email: scarano22@163.com
please see the link below:
https://www.nytimes.com/2014/10/19/business/of-virtue-and-vice-and-a-vatican-priest.html
Yours sincerely,
priest Nunzio Scarano
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