Ya Cui

Research Fellow, University of California, Irvine

7 active projects

Explore the potential mechanisms of complex structure variants in human

Complex structure variants, such as tandem repeats, have profound impacts on evolution and many human diseases, which have acquired considerable attention, including amyotrophic lateral sclerosis (ALS), Huntington’s disease, and multiple cancers. However, systematic analysis complex structure variants in multidimensional genomic…

Scientific Questions Being Studied

Complex structure variants, such as tandem repeats, have profound impacts on evolution and many human diseases, which have acquired considerable attention, including amyotrophic lateral sclerosis (ALS), Huntington’s disease, and multiple cancers. However, systematic analysis complex structure variants in multidimensional genomic data make things more complex and has become a big challenge in the field.

Project Purpose(s)

  • Ancestry

Scientific Approaches

In this project, we will build new data resources for human complex structure variants, such as tandem repeats, to systematically discover the potential biomarker and drug target in human diseases. We first will provide a friendly database, such as a tandem repeat length frequency database, for users. We also will identify molecular differences between healthy individuals and patients based on these sequencing data. We also will identify differences in human complex structure variants, such as tandem repeats, between different ancestries. The All of Us project provides a great resource of genomic data in well-phenotype, disease-relevant populations. We will identify differences between healthy individuals and patients based on All of Us sequencing data. And we will also use computational methods to systematically integrate genomic data from other cohorts.

Anticipated Findings

In this study, we will build new data resources for human complex structure variants, such as tandem repeats, to systematically discover diseases causing changes, which may be used as drug target in the future. We first will build a friendly database, such as a tandem repeat length frequency database, for users. We also will identify differences in human complex structure variants, such as tandem repeats, between different ancestries. Findings from this project will be disseminated widely and shared with the scientific community by presenting results at national scientific meetings and publishing in peer-reviewed journals.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Controlled Tier

Research Team

Owner:

  • Ya Cui - Research Fellow, University of California, Irvine

Explore the potential mechanisms of noncoding variants in human diseases

Noncoding regulatory elements, such as enhancers, act as regulators of gene expression. The Encyclopedia of DNA Elements (ENCODE) project and other studies have identified millions of regulatory elements in various tissues. The roles of noncoding regulatory elements in many human…

Scientific Questions Being Studied

Noncoding regulatory elements, such as enhancers, act as regulators of gene expression. The Encyclopedia of DNA Elements (ENCODE) project and other studies have identified millions of regulatory elements in various tissues. The roles of noncoding regulatory elements in many human diseases have acquired considerable attention, including in cancer, cardiovascular disease and psychiatric disorders. GWAS studies in understanding the genetic basis of these diseases has also identified many noncoding regulatory variants responsible for genetic risk, yet the mechanisms behind these risk variants remain poorly understood. Recent integrating multidimensional genomic data, such as expression, methylation, histone modification, chromatin accessibility and three-dimensional organization data, have enhanced interpretation of noncoding risk variants in human diseases. However, systematic analysis multidimensional genomic data make things more complex and has become a big challenge in the field.

Project Purpose(s)

  • Methods Development
  • Ancestry

Scientific Approaches

In this project, we will develop novel and powerful computational methods to systematically discover the potential biomarker and drug target in human diseases, such as cardiovascular disease, arteriosclerosis, lung diseases, asthma, T2D, and many other metabolism diseases based on multidimensional genomic data. We first will identify molecular differences between healthy individuals and patients based on these sequencing data. The All of Us project provides a great resource of genomic data in well-phenotype, disease-relevant populations. We will identify differences between healthy individuals and patients based on All of Us sequencing data. And then using newly developed computational methods to systematically integrate multidimensional genomic data from other cohorts.

Anticipated Findings

In this study, we will develop novel computational methods to systematically discover these diseases causing changes in noncoding elements, which may be used as drug target in the future. Computational tools will be shared with all researchers. Findings from this project will be disseminated widely and shared with the scientific community by presenting results at national scientific meetings and publishing in peer-reviewed journals.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Controlled Tier

Research Team

Owner:

  • Ya Cui - Research Fellow, University of California, Irvine

Explore the potential mechanisms of noncoding variants in human diseases merge

Noncoding regulatory elements, such as enhancers, act as regulators of gene expression. The Encyclopedia of DNA Elements (ENCODE) project and other studies have identified millions of regulatory elements in various tissues. The roles of noncoding regulatory elements in many human…

Scientific Questions Being Studied

Noncoding regulatory elements, such as enhancers, act as regulators of gene expression. The Encyclopedia of DNA Elements (ENCODE) project and other studies have identified millions of regulatory elements in various tissues. The roles of noncoding regulatory elements in many human diseases have acquired considerable attention, including in cancer, cardiovascular disease and psychiatric disorders. GWAS studies in understanding the genetic basis of these diseases has also identified many noncoding regulatory variants responsible for genetic risk, yet the mechanisms behind these risk variants remain poorly understood. Recent integrating multidimensional genomic data, such as expression, methylation, histone modification, chromatin accessibility and three-dimensional organization data, have enhanced interpretation of noncoding risk variants in human diseases. However, systematic analysis multidimensional genomic data make things more complex and has become a big challenge in the field.

Project Purpose(s)

  • Ancestry

Scientific Approaches

In this project, we will develop novel and powerful computational methods to systematically discover the potential biomarker and drug target in human diseases, such as cardiovascular disease, arteriosclerosis, lung diseases, asthma, T2D, and many other metabolism diseases based on multidimensional genomic data. We first will identify molecular differences between healthy individuals and patients based on these sequencing data. The All of Us project provides a great resource of genomic data in well-phenotype, disease-relevant populations. We will identify differences between healthy individuals and patients based on All of Us sequencing data. And then using newly developed computational methods to systematically integrate multidimensional genomic data from other cohorts.

Anticipated Findings

In this study, we will develop novel computational methods to systematically discover these diseases causing changes in noncoding elements, which may be used as drug target in the future. Computational tools will be shared with all researchers. Findings from this project will be disseminated widely and shared with the scientific community by presenting results at national scientific meetings and publishing in peer-reviewed journals.

This research project seeks to reduce health disparities and improve health equity in underrepresented in biomedical research (UBR) populations
This research project seeks to develop improved risk assessment and prevention strategies to preempt disease

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Controlled Tier

Research Team

Owner:

  • Ya Cui - Research Fellow, University of California, Irvine

Explore the potential mechanisms of noncoding variants in human diseases test08

Noncoding regulatory elements, such as enhancers, act as regulators of gene expression. The Encyclopedia of DNA Elements (ENCODE) project and other studies have identified millions of regulatory elements in various tissues. The roles of noncoding regulatory elements in many human…

Scientific Questions Being Studied

Noncoding regulatory elements, such as enhancers, act as regulators of gene expression. The Encyclopedia of DNA Elements (ENCODE) project and other studies have identified millions of regulatory elements in various tissues. The roles of noncoding regulatory elements in many human diseases have acquired considerable attention, including in cancer, cardiovascular disease and psychiatric disorders. GWAS studies in understanding the genetic basis of these diseases has also identified many noncoding regulatory variants responsible for genetic risk, yet the mechanisms behind these risk variants remain poorly understood. Recent integrating multidimensional genomic data, such as expression, methylation, histone modification, chromatin accessibility and three-dimensional organization data, have enhanced interpretation of noncoding risk variants in human diseases. However, systematic analysis multidimensional genomic data make things more complex and has become a big challenge in the field.

Project Purpose(s)

  • Ancestry

Scientific Approaches

In this project, we will develop novel and powerful computational methods to systematically discover the potential biomarker and drug target in human diseases, such as cardiovascular disease, arteriosclerosis, lung diseases, asthma, T2D, and many other metabolism diseases based on multidimensional genomic data. We first will identify molecular differences between healthy individuals and patients based on these sequencing data. The All of Us project provides a great resource of genomic data in well-phenotype, disease-relevant populations. We will identify differences between healthy individuals and patients based on All of Us sequencing data. And then using newly developed computational methods to systematically integrate multidimensional genomic data from other cohorts.

Anticipated Findings

In this study, we will develop novel computational methods to systematically discover these diseases causing changes in noncoding elements, which may be used as drug target in the future. Computational tools will be shared with all researchers. Findings from this project will be disseminated widely and shared with the scientific community by presenting results at national scientific meetings and publishing in peer-reviewed journals.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Controlled Tier

Research Team

Owner:

  • Ya Cui - Research Fellow, University of California, Irvine

Explore the potential mechanisms of noncoding variants in human diseases test98

Noncoding regulatory elements, such as enhancers, act as regulators of gene expression. The Encyclopedia of DNA Elements (ENCODE) project and other studies have identified millions of regulatory elements in various tissues. The roles of noncoding regulatory elements in many human…

Scientific Questions Being Studied

Noncoding regulatory elements, such as enhancers, act as regulators of gene expression. The Encyclopedia of DNA Elements (ENCODE) project and other studies have identified millions of regulatory elements in various tissues. The roles of noncoding regulatory elements in many human diseases have acquired considerable attention, including in cancer, cardiovascular disease and psychiatric disorders. GWAS studies in understanding the genetic basis of these diseases has also identified many noncoding regulatory variants responsible for genetic risk, yet the mechanisms behind these risk variants remain poorly understood. Recent integrating multidimensional genomic data, such as expression, methylation, histone modification, chromatin accessibility and three-dimensional organization data, have enhanced interpretation of noncoding risk variants in human diseases. However, systematic analysis multidimensional genomic data make things more complex and has become a big challenge in the field.

Project Purpose(s)

  • Ancestry

Scientific Approaches

In this project, we will develop novel and powerful computational methods to systematically discover the potential biomarker and drug target in human diseases, such as cardiovascular disease, arteriosclerosis, lung diseases, asthma, T2D, and many other metabolism diseases based on multidimensional genomic data. We first will identify molecular differences between healthy individuals and patients based on these sequencing data. The All of Us project provides a great resource of genomic data in well-phenotype, disease-relevant populations. We will identify differences between healthy individuals and patients based on All of Us sequencing data. And then using newly developed computational methods to systematically integrate multidimensional genomic data from other cohorts.

Anticipated Findings

In this study, we will develop novel computational methods to systematically discover these diseases causing changes in noncoding elements, which may be used as drug target in the future. Computational tools will be shared with all researchers. Findings from this project will be disseminated widely and shared with the scientific community by presenting results at national scientific meetings and publishing in peer-reviewed journals.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Controlled Tier

Research Team

Owner:

  • Ya Cui - Research Fellow, University of California, Irvine

Explore the potential mechanisms of noncoding variants in human diseases test

Noncoding regulatory elements, such as enhancers, act as regulators of gene expression. The Encyclopedia of DNA Elements (ENCODE) project and other studies have identified millions of regulatory elements in various tissues. The roles of noncoding regulatory elements in many human…

Scientific Questions Being Studied

Noncoding regulatory elements, such as enhancers, act as regulators of gene expression. The Encyclopedia of DNA Elements (ENCODE) project and other studies have identified millions of regulatory elements in various tissues. The roles of noncoding regulatory elements in many human diseases have acquired considerable attention, including in cancer, cardiovascular disease and psychiatric disorders. GWAS studies in understanding the genetic basis of these diseases has also identified many noncoding regulatory variants responsible for genetic risk, yet the mechanisms behind these risk variants remain poorly understood. Recent integrating multidimensional genomic data, such as expression, methylation, histone modification, chromatin accessibility and three-dimensional organization data, have enhanced interpretation of noncoding risk variants in human diseases. However, systematic analysis multidimensional genomic data make things more complex and has become a big challenge in the field.

Project Purpose(s)

  • Ancestry

Scientific Approaches

In this project, we will develop novel and powerful computational methods to systematically discover the potential biomarker and drug target in human diseases, such as cardiovascular disease, arteriosclerosis, lung diseases, asthma, T2D, and many other metabolism diseases based on multidimensional genomic data. We first will identify molecular differences between healthy individuals and patients based on these sequencing data. The All of Us project provides a great resource of genomic data in well-phenotype, disease-relevant populations. We will identify differences between healthy individuals and patients based on All of Us sequencing data. And then using newly developed computational methods to systematically integrate multidimensional genomic data from other cohorts.

Anticipated Findings

In this study, we will develop novel computational methods to systematically discover these diseases causing changes in noncoding elements, which may be used as drug target in the future. Computational tools will be shared with all researchers. Findings from this project will be disseminated widely and shared with the scientific community by presenting results at national scientific meetings and publishing in peer-reviewed journals.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Controlled Tier

Research Team

Owner:

  • Ya Cui - Research Fellow, University of California, Irvine

Explore the potential mechanisms of noncoding variants in human diseases new

Noncoding regulatory elements, such as enhancers, act as regulators of gene expression. The Encyclopedia of DNA Elements (ENCODE) project and other studies have identified millions of regulatory elements in various tissues. The roles of noncoding regulatory elements in many human…

Scientific Questions Being Studied

Noncoding regulatory elements, such as enhancers, act as regulators of gene expression. The Encyclopedia of DNA Elements (ENCODE) project and other studies have identified millions of regulatory elements in various tissues. The roles of noncoding regulatory elements in many human diseases have acquired considerable attention, including in cancer, cardiovascular disease and psychiatric disorders. GWAS studies in understanding the genetic basis of these diseases has also identified many noncoding regulatory variants responsible for genetic risk, yet the mechanisms behind these risk variants remain poorly understood. Recent integrating multidimensional genomic data, such as expression, methylation, histone modification, chromatin accessibility and three-dimensional organization data, have enhanced interpretation of noncoding risk variants in human diseases. However, systematic analysis multidimensional genomic data make things more complex and has become a big challenge in the field.

Project Purpose(s)

  • Ancestry

Scientific Approaches

n this project, we will develop novel and powerful computational methods to systematically discover the potential biomarker and drug target in human diseases, such as cardiovascular disease, arteriosclerosis, lung diseases, asthma, T2D, and many other metabolism diseases based on multidimensional genomic data. We first will identify molecular differences between healthy individuals and patients based on these sequencing data. The All of Us project provides a great resource of genomic data in well-phenotype, disease-relevant populations. We will identify differences between healthy individuals and patients based on All of Us sequencing data. And then using newly developed computational methods to systematically integrate multidimensional genomic data from other cohorts.

Anticipated Findings

In this study, we will develop novel computational methods to systematically discover these diseases causing changes in noncoding elements, which may be used as drug target in the future. Computational tools will be shared with all researchers. Findings from this project will be disseminated widely and shared with the scientific community by presenting results at national scientific meetings and publishing in peer-reviewed journals.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Controlled Tier

Research Team

Owner:

  • Ya Cui - Research Fellow, University of California, Irvine
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