Title: Single-cell genomics and regulatory networks for 388 human brains
Speaker: Mark Gerstein
Abstract:
Single-cell genomics is a powerful tool for studying heterogeneous
tissues such as the brain. Yet little is understood about how genetic
variants influence cell-level gene expression. Addressing this, we
uniformly processed single-nuclei, multiomics datasets into a resource
comprising >2.8 million nuclei from the prefrontal cortex across 388
individuals with various brain-related disorders and controls. For 28
harmonized neuronal and non-neuronal cell types, we assessed
population-level variation in expression and chromatin across gene
families and drug targets. Integration of expression and genotype data
revealed >1.4 million single-cell expression quantitative trait loci
(eQTLs), many of which were not seen in bulk gene-expression datasets.
The chromatin datasets allowed for the identification of >550,000
single-cell cis-regulatory elements enriched at loci linked to
brain-related traits. Combining expression, chromatin, and eQTL
datasets, we built cell type–specific gene regulatory and cell-to-cell
communication networks, which manifest cellular changes in aging and
neuropsychiatric disorders, including altered Wnt signaling in
schizophrenia and bipolar disorder. We further constructed an
integrative deep-learning model that accurately imputes single-cell
expression and simulates perturbations. The model prioritized ~250
disease-risk genes and drug targets with associated cell types,
suggesting potential precision-medicine approaches for
neuropsychiatric disorders.
==
i0lis24, eur24
On Wed, Jun 12, 2024 at 5:41 AM Rosie Johnson
<Rosie@fusion-conferences.com> wrote:
>
> Dear Speakers,
>
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> Please submit your abstract for the 'From Genetic Discoveries to Gene Function in Human Diseases' conference by Friday 21st June 2024 for inclusion in the conference abstract book.
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> We are looking forward to welcoming you to Portugal very soon!
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>
> Thank you in advance for your cooperation.
>
>
>
> Best wishes,
>
>
>
> Rosie Johnson | Conference Manager
>
>
>
> T: +44 (0) 1638 555057
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> DD: +44 (0) 1638 599351
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> E: rosie@fusion-conferences.com
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Sunday, June 16, 2024
Saturday, June 15, 2024
Talk at EMBL in July '24 [eur24embl]
Title: Topics in Neurogenomics & Genomic Privacy
Speaker: Mark Gerstein
Abstract:
My talk will focus on neurogenomics and how this has inspired my group
to become interested in genomic privacy and security. I'll first
discuss our work within the PsychENCODE consortium, where we created a
single-cell multiomics resource of the human prefrontal cortex. This
resource encompasses over 2.8 million nuclei from 388 individuals,
enabling the identification of expression quantitative trait loci and
cell type-specific regulatory elements. Our neurogenomics work has
encouraged us to develop computational tools, particularly expression
clustering algorithms. We used these to construct cell-type regulatory
networks and cell-to-cell communication networks, which change
substantially in aging and neuropsychiatric disorders. Furthermore, we
developed an integrative model to impute single-cell expression and
prioritize disease-risk genes and drug targets. Finally, I'll talk
about how important it is to keep large-scale cohort data,
particularly for mental illness, both private and secure. I'll
highlight some techniques that we have developed for security,
particularly in relation to assessing and mitigating privacy leakage
from genomic datasets.
Speaker: Mark Gerstein
Abstract:
My talk will focus on neurogenomics and how this has inspired my group
to become interested in genomic privacy and security. I'll first
discuss our work within the PsychENCODE consortium, where we created a
single-cell multiomics resource of the human prefrontal cortex. This
resource encompasses over 2.8 million nuclei from 388 individuals,
enabling the identification of expression quantitative trait loci and
cell type-specific regulatory elements. Our neurogenomics work has
encouraged us to develop computational tools, particularly expression
clustering algorithms. We used these to construct cell-type regulatory
networks and cell-to-cell communication networks, which change
substantially in aging and neuropsychiatric disorders. Furthermore, we
developed an integrative model to impute single-cell expression and
prioritize disease-risk genes and drug targets. Finally, I'll talk
about how important it is to keep large-scale cohort data,
particularly for mental illness, both private and secure. I'll
highlight some techniques that we have developed for security,
particularly in relation to assessing and mitigating privacy leakage
from genomic datasets.
Talk at UCL in July '24 [eur24ucl]
Title: Topics in Neurogenomics & Genomic Privacy
Speaker: Mark Gerstein
Abstract:
My talk will focus on neurogenomics and how this has inspired my group
to become interested in genomic privacy and security. I'll first
discuss our work within the PsychENCODE consortium, where we created a
single-cell multiomics resource of the human prefrontal cortex. This
resource encompasses over 2.8 million nuclei from 388 individuals,
enabling the identification of expression quantitative trait loci and
cell type-specific regulatory elements. Our neurogenomics work has
encouraged us to develop computational tools, particularly expression
clustering algorithms. We used these to construct cell-type regulatory
networks and cell-to-cell communication networks, which change
substantially in aging and neuropsychiatric disorders. Furthermore, we
developed an integrative model to impute single-cell expression and
prioritize disease-risk genes and drug targets. Finally, I'll talk
about how important it is to keep large-scale cohort data,
particularly for mental illness, both private and secure. I'll
highlight some techniques that we have developed for security,
particularly in relation to assessing and mitigating privacy leakage
from genomic datasets.
Speaker: Mark Gerstein
Abstract:
My talk will focus on neurogenomics and how this has inspired my group
to become interested in genomic privacy and security. I'll first
discuss our work within the PsychENCODE consortium, where we created a
single-cell multiomics resource of the human prefrontal cortex. This
resource encompasses over 2.8 million nuclei from 388 individuals,
enabling the identification of expression quantitative trait loci and
cell type-specific regulatory elements. Our neurogenomics work has
encouraged us to develop computational tools, particularly expression
clustering algorithms. We used these to construct cell-type regulatory
networks and cell-to-cell communication networks, which change
substantially in aging and neuropsychiatric disorders. Furthermore, we
developed an integrative model to impute single-cell expression and
prioritize disease-risk genes and drug targets. Finally, I'll talk
about how important it is to keep large-scale cohort data,
particularly for mental illness, both private and secure. I'll
highlight some techniques that we have developed for security,
particularly in relation to assessing and mitigating privacy leakage
from genomic datasets.
Talk at NEC Labs America [i0nec24]
Title: Topics in Neurogenomics & Genomic Privacy
Speaker: Mark Gerstein
Abstract:
My talk will focus on neurogenomics and how this has inspired my group
to become interested in genomic privacy and security. I'll first
discuss our work within the PsychENCODE consortium, where we created a
single-cell multiomics resource of the human prefrontal cortex. This
resource encompasses over 2.8 million nuclei from 388 individuals,
enabling the identification of expression quantitative trait loci and
cell type-specific regulatory elements. Our neurogenomics work has
encouraged us to develop computational tools, particularly expression
clustering algorithms. We used these to construct cell-type regulatory
networks and cell-to-cell communication networks, which change
substantially in aging and neuropsychiatric disorders. Furthermore, we
developed an integrative model to impute single-cell expression and
prioritize disease-risk genes and drug targets. Finally, I'll talk
about how important it is to keep large-scale cohort data,
particularly for mental illness, both private and secure. I'll
highlight some techniques that we have developed for security,
particularly in relation to assessing and mitigating privacy leakage
from genomic datasets.
Speaker: Mark Gerstein
Abstract:
My talk will focus on neurogenomics and how this has inspired my group
to become interested in genomic privacy and security. I'll first
discuss our work within the PsychENCODE consortium, where we created a
single-cell multiomics resource of the human prefrontal cortex. This
resource encompasses over 2.8 million nuclei from 388 individuals,
enabling the identification of expression quantitative trait loci and
cell type-specific regulatory elements. Our neurogenomics work has
encouraged us to develop computational tools, particularly expression
clustering algorithms. We used these to construct cell-type regulatory
networks and cell-to-cell communication networks, which change
substantially in aging and neuropsychiatric disorders. Furthermore, we
developed an integrative model to impute single-cell expression and
prioritize disease-risk genes and drug targets. Finally, I'll talk
about how important it is to keep large-scale cohort data,
particularly for mental illness, both private and secure. I'll
highlight some techniques that we have developed for security,
particularly in relation to assessing and mitigating privacy leakage
from genomic datasets.
Wednesday, April 10, 2024
The Festival of Genomics & BioData, June 2024, Boston [i0fog24]
Title: Topics in Neurogenomics
Bullets:
* Single cell analysis of almost 400 brain transcriptomes, including
single-cell eQTLs
* Cell type specific regulatory networks
* Integrative deep-learning model for data imputation and to predict
disease risk
Bullets:
* Single cell analysis of almost 400 brain transcriptomes, including
single-cell eQTLs
* Cell type specific regulatory networks
* Integrative deep-learning model for data imputation and to predict
disease risk
Tuesday, July 4, 2023
Re: ISMB/ECCB 2023 Keynote Information
Added, thanks!
Seth Munholland, Ph.D., DES
Lead Technologist
International Society for Computational Biology
T: (403) 831-2587On Tue, Jul 4, 2023 at 10:46 AM Steven Leard <steven@marketwhys.ca> wrote:
thanks Mark - Seth will get this added shorty,
On Jul 4, 2023, at 10:45 AM, Mark Gerstein <mark@gersteinlab.org> wrote:Title:
A Gradual Evolution in Bioinformatics Research
Abstract:
This talk will survey my lab's computational biology research from the
1990s to the present and touch upon the broader directions of the
field. I'll start by discussing some early work on structure and
simulation and how this transitioned into studying protein and gene
networks and, eventually, human genome annotation with
machine-learning models. Finally, I'll discuss some of our current
work developing models for variant impact based on allele-specific
binding and how this highlights the role of transcription-factor
binding motifs that are particularly sensitive to mutation. I'll end
with thoughts on where I think the field is going. In particular, I'll
discuss the importance of dealing with large amounts of private data
and using digital sensors to phenotype individuals more accurately.
==
i0ismb23
Re: ISMB/ECCB 2023 Keynote Information
thanks Mark - Seth will get this added shorty,
On Jul 4, 2023, at 10:45 AM, Mark Gerstein <mark@gersteinlab.org> wrote:Title:
A Gradual Evolution in Bioinformatics Research
Abstract:
This talk will survey my lab's computational biology research from the
1990s to the present and touch upon the broader directions of the
field. I'll start by discussing some early work on structure and
simulation and how this transitioned into studying protein and gene
networks and, eventually, human genome annotation with
machine-learning models. Finally, I'll discuss some of our current
work developing models for variant impact based on allele-specific
binding and how this highlights the role of transcription-factor
binding motifs that are particularly sensitive to mutation. I'll end
with thoughts on where I think the field is going. In particular, I'll
discuss the importance of dealing with large amounts of private data
and using digital sensors to phenotype individuals more accurately.
==
i0ismb23
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