[Theory] REMINDER: 5/14 Talks at TTIC: Derek Reiman, University of Illinois at Chicago

[Mary Marre]

*When:*      Friday, May 14th at* 2:00 pm CT*



*Where:*     Zoom Virtual Talk (*register in advance here
<https://uchicagogroup.zoom.us/webinar/register/WN_k3Hb0Ab2TzqZWdqo8Wh7DQ>*)



*Who: *       Derek Reiman, University of Illinois at Chicago


*Title: *Deep Learning Frameworks for Multi-omics Analyses of the
Microbiome in Disease Studies

*Abstract: *Over the last decade, our understanding of the functions of the
microbiome has greatly increased. In particular, the microbiome of the gut
has been shown to play a critical role in the development of multiple
metabolic related diseases.As such, clinicians have looked to the
microbiome as a potential target for therapeutic interventions by either
directly altering the microbiome composition or targeting underlying
metabolic functions. In this talk, I will introduce integrative deep
learning frameworks addressing challenges in microbiome studies. First, I
will discuss a convolutional neural network framework that integrates
microbial abundance with the underlying community taxonomic structure for
the identification of microbial biomarkers associated with specific
diseases. Second, I will present an interpretable deep neural network
framework integrating microbiome and metabolomic data to facilitate the
clustering of microbes and metabolites into functionally related modules. I
will conclude by discussing my future research direction involving the
integration of external stimuli, imaging, and single cell sequencing data
tobetter model microbiome dynamics and functions.

*Bio: *Derek Reiman is a PhD candidate at the University of Illinois at
Chicago. Hisdoctoral research focuses on developing new deep learning
frameworks for multi-omics analyses of the host-microbiome interface. His
work has been supported by grants from the NVIDIA Corporation and by UIC’s
College of Medicine Pre-doctoral Education for Clinical and Translational
Sciences program.Previously, he spent time interning at Tempus Labs in the
Immunology group,where he focused on developing deep learning models for
integrating gene expression and imaging data. His research interests lie in
developing interpretable deep learning models for biology.
Host: Jinbo Xu <j3xu at ttic.edu>





Mary C. Marre
Faculty Administrative Support
*Toyota Technological Institute*
*6045 S. Kenwood Avenue*
*Room 517*
*Chicago, IL  60637*
*p:(773) 834-1757*
*f: (773) 357-6970*
*mmarre at ttic.edu <mmarre at ttic.edu>*


On Thu, May 13, 2021 at 4:43 PM Mary Marre <mmarre at ttic.edu> wrote:

> *When:*      Friday, May 14th at* 2:00 pm CT*
>
>
>
> *Where:*     Zoom Virtual Talk (*register in advance here
> <https://uchicagogroup.zoom.us/webinar/register/WN_k3Hb0Ab2TzqZWdqo8Wh7DQ>*
> )
>
>
>
> *Who: *       Derek Reiman, University of Illinois at Chicago
>
>
> *Title: *Deep Learning Frameworks for Multi-omics Analyses of the
> Microbiome in Disease Studies
>
> *Abstract: *Over the last decade, our understanding of the functions of
> the microbiome has greatly increased. In particular, the microbiome of the
> gut has been shown to play a critical role in the development of multiple
> metabolic related diseases.As such, clinicians have looked to the
> microbiome as a potential target for therapeutic interventions by either
> directly altering the microbiome composition or targeting underlying
> metabolic functions. In this talk, I will introduce integrative deep
> learning frameworks addressing challenges in microbiome studies. First, I
> will discuss a convolutional neural network framework that integrates
> microbial abundance with the underlying community taxonomic structure for
> the identification of microbial biomarkers associated with specific
> diseases. Second, I will present an interpretable deep neural network
> framework integrating microbiome and metabolomic data to facilitate the
> clustering of microbes and metabolites into functionally related modules. I
> will conclude by discussing my future research direction involving the
> integration of external stimuli, imaging, and single cell sequencing data
> tobetter model microbiome dynamics and functions.
>
> *Bio: *Derek Reiman is a PhD candidate at the University of Illinois at
> Chicago. Hisdoctoral research focuses on developing new deep learning
> frameworks for multi-omics analyses of the host-microbiome interface. His
> work has been supported by grants from the NVIDIA Corporation and by UIC’s
> College of Medicine Pre-doctoral Education for Clinical and Translational
> Sciences program.Previously, he spent time interning at Tempus Labs in the
> Immunology group,where he focused on developing deep learning models for
> integrating gene expression and imaging data. His research interests lie in
> developing interpretable deep learning models for biology.
> Host: Jinbo Xu <j3xu at ttic.edu>
>
>
>
>
>
>
>
>
> Mary C. Marre
> Faculty Administrative Support
> *Toyota Technological Institute*
> *6045 S. Kenwood Avenue*
> *Room 517*
> *Chicago, IL  60637*
> *p:(773) 834-1757*
> *f: (773) 357-6970*
> *mmarre at ttic.edu <mmarre at ttic.edu>*
>
>
> On Sun, May 9, 2021 at 7:27 PM Mary Marre <mmarre at ttic.edu> wrote:
>
>> *When:*      Friday, May 14th at* 2:00 pm CT*
>>
>>
>>
>> *Where:*     Zoom Virtual Talk (*register in advance here
>> <https://uchicagogroup.zoom.us/webinar/register/WN_k3Hb0Ab2TzqZWdqo8Wh7DQ>*
>> )
>>
>>
>>
>> *Who: *       Derek Reiman, University of Illinois at Chicago
>>
>>
>> *Title: *Deep Learning Frameworks for Multi-omics Analyses of the
>> Microbiome in Disease Studies
>>
>> *Abstract: *Over the last decade, our understanding of the functions of
>> the microbiome has greatly increased. In particular, the microbiome of the
>> gut has been shown to play a critical role in the development of multiple
>> metabolic related diseases.As such, clinicians have looked to the
>> microbiome as a potential target for therapeutic interventions by either
>> directly altering the microbiome composition or targeting underlying
>> metabolic functions. In this talk, I will introduce integrative deep
>> learning frameworks addressing challenges in microbiome studies. First, I
>> will discuss a convolutional neural network framework that integrates
>> microbial abundance with the underlying community taxonomic structure for
>> the identification of microbial biomarkers associated with specific
>> diseases. Second, I will present an interpretable deep neural network
>> framework integrating microbiome and metabolomic data to facilitate the
>> clustering of microbes and metabolites into functionally related modules. I
>> will conclude by discussing my future research direction involving the
>> integration of external stimuli, imaging, and single cell sequencing data
>> tobetter model microbiome dynamics and functions.
>>
>> *Bio: *Derek Reiman is a PhD candidate at the University of Illinois at
>> Chicago. Hisdoctoral research focuses on developing new deep learning
>> frameworks for multi-omics analyses of the host-microbiome interface. His
>> work has been supported by grants from the NVIDIA Corporation and by UIC’s
>> College of MedicinePre-doctoral Education for Clinical and Translational
>> Sciences program.Previously, he spent time interning at Tempus Labs in the
>> Immunology group,where he focused on developing deep learning models for
>> integrating gene expression and imaging data. His research interests lie in
>> developing interpretable deep learning models for biology.
>> Host: Jinbo Xu <j3xu at ttic.edu>
>>
>>
>>
>>
>>
>> Mary C. Marre
>> Faculty Administrative Support
>> *Toyota Technological Institute*
>> *6045 S. Kenwood Avenue*
>> *Chicago, IL  60637*
>> *mmarre at ttic.edu <mmarre at ttic.edu>*
>>
>
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