The CCBS Opportunity award competition is open to any UCI graduate student or postdoctoral researcher (including project scientists, specialists, etc.), who is present at the 2022 Sys Bio Retreat. Any pair (or trio) of individuals who meet the above criteria may jointly submit a proposal for this year's competition following the instructions below. The progress reports from previous years' awardees are available below.
2022 - 2023
From Theory to Data; from Data to Theory
This means research that develops theory in biology based on new or existing biological data, or uses theory to inform the collection or analysis of biological data.
Past Awardees
| Title | Participants | Department(s) |
|---|---|---|
| Characterizing the Transition Between Naïve and Primed States of Pluripotent ESCs in Different Mammalian Species | Christina Wilcox, Kate Williams PI - Ali Mortazavi Linh Vuong, PI - Peter Donovan | Developmental & Cell Biology Developmental & Cell Biology |
| Transcriptomic analysis of MCF-10A mammary epithelial acini in normal and invasive states | Sorena Rahmanian, PI - Ali Mortazavi Qingda Hu, PI - Elliot Botvinick | Developmental & Cell Biology Biomedical Engineering and Surgery |
| Understanding cellular state transitions in the mammary gland microenvironment from a control theory perspective | Kevin Nee, PI - Kai Kessenbrock Suoqin Jin, PI - Qing Nie | Biological Chemistry Mathematics and Developmental & Cell Biology |
| Transitional states regulating macrophage heterogeneity in dystrophic muscle | Nick Pervolarakis, Quy Nguyen, PI - Kai Kessenbrock Jenna Kastenschmidt, PI - S. Armando Villalta | Biological Chemistry Physiology & Biophysics |
| Methylation pseudotime: a novel tool for observing protein-DNA interactions | Julien Morival, PI - Tim Downing Adam MacLean, PI - Qing Nie | Biomedical Engineering Mathematics and Developmental & Cell Biology |
| Label-free, non-destructive determination of cell state using high throughput characterization of cell physical properties | Matt Bovyn, PI - Jun Allard Cody Combs, PI - Zuzanna Siwy | Physics and Astronomy and Mathematics Physics and Astronomy |
| Optimal experimental design for feedback models of hematopoiesis | Luis Martinez-Lomeli, PI - Babak Shahbaba/Volodymyr Minin Abdon Iniguez, Shuxiong Wang, PI - John Lowengrub Prasanthi Tata, PI - Richard Van Etten | Statistics Mathematics, Biomedical Engineering and Chemical Engineering & Material Science Hematology/Oncology, Department of Medicine |
Theme:
Variability and plasticity - That is: Research to understand diversity and difference, and its impact on phenotype and function. Variability here refers to measurable differences across sets of genes, cells, molecules, networks, genotypes or organisms.
RNA Processing and Cell State Plasticity in the Colon Crypt
- Amber Habrowski (Microbiology & Molecular Genetics) - Mariam Waterman Lab
- Gabriela Balderrama (Developmental & Cell Biology) - Ali Mortazabi Lab
Multi-scale Analysis of Histone Acetylation Variability in the Cancer Genome to Predict Changes in Chromatin Function and Architecture
- Navied Akhtar (Biomedical Engineering) - Tim Downing Lab
- Alvaro Fletcher (Mathematics) - German Enciso Lab
- Tessa Morris (Biomedical Engineering) - Anya Grosberg Lab
Elucidating Fibroblast and Pericyte Plasticity and their Roles in Cancer Using Temporal Single Cell RNA Sequencing of Microphysiological Cancer Models
- Kevin Nee (Biological Chemistry) - Kai Kessenbrock Lab
- Stephanie Hachey (Molecular Biology & Biochemistry) - Chris Hughes Lab
Plasticity and Diversity of Metastatic Breast Cancer Cells Revealed by Transcriptome Analysis
- Gabriela Balderrama (Developmental & Cell Biology) - Ali Mortazavi Lab
- Anastasia Ionkina (Chemistry) - Jennifer Prescher Lab
Identifying Altered Transcriptional Dynamics and Signaling Pathways in Vitiligo Affected Epidermis
- Jessica Flesher (SOM Dermatology) - Anand Ganesan Lab
- Lihua Zhang (Mathematics) - Qing Nie Lab
- Suoqin Jin (CCBS) - Qing Nie Lab
Targeted Epigenetic Tools for the Control of Variability in Cardiac Differentiation of Patient-Derived iPSCs
- Julien Morival (Biomedical Engineering) - Tim Downing Lab
- Lily Widyastuti (Biological Chemistry) - Michael Zaragoza Lab
Variability and Plasticity of RAC1 and RHOA Signaling on Keratinocytes During Epidermal Regeneration
- Rachel Cinco (Biomedical Engineering) - Michelle Digman Lab
- Morgan Dragan (Biological Chemistry) - Xing Dai Lab
Examining the Mechanical Properties of Cells with Lamin A/C Mutations
- Cody Combs (Physics and Astronomy) - Zusanna Siwy Lab
- Richard Tran (Biomedical Engineering) - Anya Grosberg Lab
- Michael Zaragoza Lab
Theme:
Enriching Models with Health Data - Take advantage of existing data from medicine, health systems, epidemiology, or any other health related professions to build, enhance, or improve mathematical, computational or statistical models that inform scientific understanding, clinical practice, and/or public policy. Datasets such as the Cancer Genome Atlas, Cell and Brain Atlases, health records, and COVID-19 epidemiological data are some of the many types of starting points that could be considered.
| Title | Participants | Department(s) |
|---|---|---|
| Connecting Oncogenic Transcription Factor Myc-Max Search Dynamics on DNA with its Genome Association Profiling | Carmen Al Masiri, PI - Jin Yu Yi Dai, PI - Jing Zhang | Physics and Astronomy Computer Science |
| Predicting Circadian Phase Clock Heterogeneity in Normal and Diseased Human Epidermis at a Single-cell Level | Junyan Duann, PIs - Bogi Anderson & John Lowengrub Michelle Ngo, PIs - Babak Shahbaba & John Lowengrub Rolando Ruiz, PIs - Arthur Lander & Anand Ganesan | Biological Chemistry Statistics Development and Cell Biology |
| Modeling Clonal Evolution in MPN | Jonathan Vo, PI - John Lowengrub Eric Bourgain-Chang, PI - Qing Nie Brianna Hoover, PI - Angela Fleischman | Mathematics Mathematics Medicine |
| Identifying Statin-Sensitivity Biomarkers in Blood Cancers | Dennis Juarez, PI - David Fruman Yingxin Cao, PI - Xiaohui Xie | Molecular Biology & Biochemistry Computer Science |
| DNA Methylation and Copy Number Variation in Machine Learning Approaches for Predicting Tumor Progression in Colorectal Cancer | Charmeine Ko, PI - James Brody Annie Trinh, PI - Tim Downing | Biomedical Engineering Biomedical Engineering |