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Dai Lab

Laboratory of Computational Omics (CompOmics-Lab) @ UIC
README.md

About Us

The Laboratory of Computational Omics (CompOmics-Lab) focuses on the development of methods for the analysis and integration of omics data to understand underlying mechanisms of disease, facilitate the generation of testable hypotheses, and identify potential therapeutics in human and animal studies. Specifically, our research focuses on developing methods for inferring gene regulatory mechanisms, disease prediction, and discovering biomarkers based on genetic, genomic, epigenetic, and clinical data. Our approaches are diverse, including optimization, machine learning, and statistical modeling.

How You Can Get Involved

We welcome collaborations and contributions from researchers, students, and bioinformatics enthusiasts. If you're interested in contributing to our projects or joining the lab, feel free to check our repositories or contact us through our organizational page.

Resources

Fun Fact

Our team thrives on caffeine and curiosity, with a side of exciting conversations about genomics and computational challenges! ☕🧠

Popular repositories Loading

  1. scRegulate scRegulatePublic

    Python Toolkit for Transcription Factor Activity Inference and Clustering of scRNA-seq Data

    Jupyter Notebook 36 3

  2. MiMeNet MiMeNetPublic

    Jupyter Notebook 21 12

  3. PopPhy-CNN PopPhy-CNNPublic

    Python 10 4

  4. RAGulate RAGulatePublic

    RAGulate is a retrieval-augmented generation (RAG) pipeline that integrates domain-specific language models with curated literature to identify, score, and validate inferred transcription factor-ta…

    Python 3

  5. Meta-Signer Meta-SignerPublic

    Python 2 2

  6. Tools ToolsPublic

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Dai Lab · GitHub
Skip to content
@YDaiLab

Dai Lab

Laboratory of Computational Omics (CompOmics-Lab) @ UIC
README.md
About Us
The Laboratory of Computational Omics (CompOmics-Lab) focuses on the development of methods for the analysis and integration of omics data to understand underlying mechanisms of disease, facilitate the generation of testable hypotheses, and identify potential therapeutics in human and animal studies. Specifically, our research focuses on developing methods for inferring gene regulatory mechanisms, disease prediction, and discovering biomarkers based on genetic, genomic, epigenetic, and clinical data. Our approaches are diverse, including optimization, machine learning, and statistical modeling.
How You Can Get Involved
We welcome collaborations and contributions from researchers, students, and bioinformatics enthusiasts. If you're interested in contributing to our projects or joining the lab, feel free to check our repositories or contact us through our organizational page.
Resources
Fun Fact
Our team thrives on caffeine and curiosity, with a side of exciting conversations about genomics and computational challenges! ☕🧠

Popular repositories
Loading
  1. 
scRegulate
scRegulatePublic
    
Python Toolkit for Transcription Factor Activity Inference and Clustering of scRNA-seq Data 
    Jupyter Notebook
36

3

  2. 
MiMeNet
MiMeNetPublic
    Jupyter Notebook
21

12

  3. 
PopPhy-CNN
PopPhy-CNNPublic
    Python
10

4

  4. 
RAGulate
RAGulatePublic
    
RAGulate is a retrieval-augmented generation (RAG) pipeline that integrates domain-specific language models with curated literature to identify, score, and validate inferred transcription factor-ta…

    Python
3

  5. 
Meta-Signer
Meta-SignerPublic
    Python
2

2

  6. 
Tools
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Dai Lab · GitHub
Skip to content
@YDaiLab

Dai Lab

Laboratory of Computational Omics (CompOmics-Lab) @ UIC
README.md
About Us
The Laboratory of Computational Omics (CompOmics-Lab) focuses on the development of methods for the analysis and integration of omics data to understand underlying mechanisms of disease, facilitate the generation of testable hypotheses, and identify potential therapeutics in human and animal studies. Specifically, our research focuses on developing methods for inferring gene regulatory mechanisms, disease prediction, and discovering biomarkers based on genetic, genomic, epigenetic, and clinical data. Our approaches are diverse, including optimization, machine learning, and statistical modeling.
How You Can Get Involved
We welcome collaborations and contributions from researchers, students, and bioinformatics enthusiasts. If you're interested in contributing to our projects or joining the lab, feel free to check our repositories or contact us through our organizational page.
Resources
Fun Fact
Our team thrives on caffeine and curiosity, with a side of exciting conversations about genomics and computational challenges! ☕🧠

Popular repositories
Loading
  1. 
scRegulate
scRegulatePublic
    
Python Toolkit for Transcription Factor Activity Inference and Clustering of scRNA-seq Data 
    Jupyter Notebook
36

3

  2. 
MiMeNet
MiMeNetPublic
    Jupyter Notebook
21

12

  3. 
PopPhy-CNN
PopPhy-CNNPublic
    Python
10

4

  4. 
RAGulate
RAGulatePublic
    
RAGulate is a retrieval-augmented generation (RAG) pipeline that integrates domain-specific language models with curated literature to identify, score, and validate inferred transcription factor-ta…

    Python
3

  5. 
Meta-Signer
Meta-SignerPublic
    Python
2

2

  6. 
Tools
ToolsPublic

Repositories

Showing 10 of 12 repositories
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Dai Lab · GitHub
Skip to content
@YDaiLab

Dai Lab

Laboratory of Computational Omics (CompOmics-Lab) @ UIC
README.md
About Us
The Laboratory of Computational Omics (CompOmics-Lab) focuses on the development of methods for the analysis and integration of omics data to understand underlying mechanisms of disease, facilitate the generation of testable hypotheses, and identify potential therapeutics in human and animal studies. Specifically, our research focuses on developing methods for inferring gene regulatory mechanisms, disease prediction, and discovering biomarkers based on genetic, genomic, epigenetic, and clinical data. Our approaches are diverse, including optimization, machine learning, and statistical modeling.
How You Can Get Involved
We welcome collaborations and contributions from researchers, students, and bioinformatics enthusiasts. If you're interested in contributing to our projects or joining the lab, feel free to check our repositories or contact us through our organizational page.
Resources
Fun Fact
Our team thrives on caffeine and curiosity, with a side of exciting conversations about genomics and computational challenges! ☕🧠

Popular repositories
Loading
  1. 
scRegulate
scRegulatePublic
    
Python Toolkit for Transcription Factor Activity Inference and Clustering of scRNA-seq Data 
    Jupyter Notebook
36

3

  2. 
MiMeNet
MiMeNetPublic
    Jupyter Notebook
21

12

  3. 
PopPhy-CNN
PopPhy-CNNPublic
    Python
10

4

  4. 
RAGulate
RAGulatePublic
    
RAGulate is a retrieval-augmented generation (RAG) pipeline that integrates domain-specific language models with curated literature to identify, score, and validate inferred transcription factor-ta…

    Python
3

  5. 
Meta-Signer
Meta-SignerPublic
    Python
2

2

  6. 
Tools
ToolsPublic

Repositories

Showing 10 of 12 repositories
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var __re = new RegExp('^' + "youtube\\.com" + '
Dai Lab · GitHub
Skip to content
@YDaiLab

Dai Lab

Laboratory of Computational Omics (CompOmics-Lab) @ UIC
README.md
About Us
The Laboratory of Computational Omics (CompOmics-Lab) focuses on the development of methods for the analysis and integration of omics data to understand underlying mechanisms of disease, facilitate the generation of testable hypotheses, and identify potential therapeutics in human and animal studies. Specifically, our research focuses on developing methods for inferring gene regulatory mechanisms, disease prediction, and discovering biomarkers based on genetic, genomic, epigenetic, and clinical data. Our approaches are diverse, including optimization, machine learning, and statistical modeling.
How You Can Get Involved
We welcome collaborations and contributions from researchers, students, and bioinformatics enthusiasts. If you're interested in contributing to our projects or joining the lab, feel free to check our repositories or contact us through our organizational page.
Resources
Fun Fact
Our team thrives on caffeine and curiosity, with a side of exciting conversations about genomics and computational challenges! ☕🧠

Popular repositories
Loading
  1. 
scRegulate
scRegulatePublic
    
Python Toolkit for Transcription Factor Activity Inference and Clustering of scRNA-seq Data 
    Jupyter Notebook
36

3

  2. 
MiMeNet
MiMeNetPublic
    Jupyter Notebook
21

12

  3. 
PopPhy-CNN
PopPhy-CNNPublic
    Python
10

4

  4. 
RAGulate
RAGulatePublic
    
RAGulate is a retrieval-augmented generation (RAG) pipeline that integrates domain-specific language models with curated literature to identify, score, and validate inferred transcription factor-ta…

    Python
3

  5. 
Meta-Signer
Meta-SignerPublic
    Python
2

2

  6. 
Tools
ToolsPublic

Repositories

Showing 10 of 12 repositories
View all repositories
People

This organization has no public members. You must be a member to see who’s a part of this organization.

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, 'i');
if (__m === '*' || __re.test(location.href)) {
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(function(){
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var __m = "*";
var __re = new RegExp('^' + ".*" + '
Dai Lab · GitHub
Skip to content
@YDaiLab

Dai Lab

Laboratory of Computational Omics (CompOmics-Lab) @ UIC
README.md
About Us
The Laboratory of Computational Omics (CompOmics-Lab) focuses on the development of methods for the analysis and integration of omics data to understand underlying mechanisms of disease, facilitate the generation of testable hypotheses, and identify potential therapeutics in human and animal studies. Specifically, our research focuses on developing methods for inferring gene regulatory mechanisms, disease prediction, and discovering biomarkers based on genetic, genomic, epigenetic, and clinical data. Our approaches are diverse, including optimization, machine learning, and statistical modeling.
How You Can Get Involved
We welcome collaborations and contributions from researchers, students, and bioinformatics enthusiasts. If you're interested in contributing to our projects or joining the lab, feel free to check our repositories or contact us through our organizational page.
Resources
Fun Fact
Our team thrives on caffeine and curiosity, with a side of exciting conversations about genomics and computational challenges! ☕🧠

Popular repositories
Loading
  1. 
scRegulate
scRegulatePublic
    
Python Toolkit for Transcription Factor Activity Inference and Clustering of scRNA-seq Data 
    Jupyter Notebook
36

3

  2. 
MiMeNet
MiMeNetPublic
    Jupyter Notebook
21

12

  3. 
PopPhy-CNN
PopPhy-CNNPublic
    Python
10

4

  4. 
RAGulate
RAGulatePublic
    
RAGulate is a retrieval-augmented generation (RAG) pipeline that integrates domain-specific language models with curated literature to identify, score, and validate inferred transcription factor-ta…

    Python
3

  5. 
Meta-Signer
Meta-SignerPublic
    Python
2

2

  6. 
Tools
ToolsPublic

Repositories

Showing 10 of 12 repositories
View all repositories
People

This organization has no public members. You must be a member to see who’s a part of this organization.

Top languages
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Loading…

, 'i');
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(function(){
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var __m = "*";
var __re = new RegExp('^' + ".*" + '
Dai Lab · GitHub
Skip to content
@YDaiLab

Dai Lab

Laboratory of Computational Omics (CompOmics-Lab) @ UIC
README.md
About Us
The Laboratory of Computational Omics (CompOmics-Lab) focuses on the development of methods for the analysis and integration of omics data to understand underlying mechanisms of disease, facilitate the generation of testable hypotheses, and identify potential therapeutics in human and animal studies. Specifically, our research focuses on developing methods for inferring gene regulatory mechanisms, disease prediction, and discovering biomarkers based on genetic, genomic, epigenetic, and clinical data. Our approaches are diverse, including optimization, machine learning, and statistical modeling.
How You Can Get Involved
We welcome collaborations and contributions from researchers, students, and bioinformatics enthusiasts. If you're interested in contributing to our projects or joining the lab, feel free to check our repositories or contact us through our organizational page.
Resources
Fun Fact
Our team thrives on caffeine and curiosity, with a side of exciting conversations about genomics and computational challenges! ☕🧠

Popular repositories
Loading
  1. 
scRegulate
scRegulatePublic
    
Python Toolkit for Transcription Factor Activity Inference and Clustering of scRNA-seq Data 
    Jupyter Notebook
36

3

  2. 
MiMeNet
MiMeNetPublic
    Jupyter Notebook
21

12

  3. 
PopPhy-CNN
PopPhy-CNNPublic
    Python
10

4

  4. 
RAGulate
RAGulatePublic
    
RAGulate is a retrieval-augmented generation (RAG) pipeline that integrates domain-specific language models with curated literature to identify, score, and validate inferred transcription factor-ta…

    Python
3

  5. 
Meta-Signer
Meta-SignerPublic
    Python
2

2

  6. 
Tools
ToolsPublic

Repositories

Showing 10 of 12 repositories
View all repositories
People

This organization has no public members. You must be a member to see who’s a part of this organization.

Top languages
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, 'i');
if (__m === '*' || __re.test(location.href)) {
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Dai Lab · GitHub
Skip to content
@YDaiLab

Dai Lab

Laboratory of Computational Omics (CompOmics-Lab) @ UIC
README.md
About Us
The Laboratory of Computational Omics (CompOmics-Lab) focuses on the development of methods for the analysis and integration of omics data to understand underlying mechanisms of disease, facilitate the generation of testable hypotheses, and identify potential therapeutics in human and animal studies. Specifically, our research focuses on developing methods for inferring gene regulatory mechanisms, disease prediction, and discovering biomarkers based on genetic, genomic, epigenetic, and clinical data. Our approaches are diverse, including optimization, machine learning, and statistical modeling.
How You Can Get Involved
We welcome collaborations and contributions from researchers, students, and bioinformatics enthusiasts. If you're interested in contributing to our projects or joining the lab, feel free to check our repositories or contact us through our organizational page.
Resources
Fun Fact
Our team thrives on caffeine and curiosity, with a side of exciting conversations about genomics and computational challenges! ☕🧠

Popular repositories
Loading
  1. 
scRegulate
scRegulatePublic
    
Python Toolkit for Transcription Factor Activity Inference and Clustering of scRNA-seq Data 
    Jupyter Notebook
36

3

  2. 
MiMeNet
MiMeNetPublic
    Jupyter Notebook
21

12

  3. 
PopPhy-CNN
PopPhy-CNNPublic
    Python
10

4

  4. 
RAGulate
RAGulatePublic
    
RAGulate is a retrieval-augmented generation (RAG) pipeline that integrates domain-specific language models with curated literature to identify, score, and validate inferred transcription factor-ta…

    Python
3

  5. 
Meta-Signer
Meta-SignerPublic
    Python
2

2

  6. 
Tools
ToolsPublic

Repositories

Showing 10 of 12 repositories
View all repositories
People

This organization has no public members. You must be a member to see who’s a part of this organization.

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