Institute for Quantitative and Computational Biosciences

QCBio Research Seminar in collaboration with B.I.G. Summer: Valerie Arboleda
2021-08-06 14:00 - 14:30 (America/Los_Angeles) | ZOOM, CA, United States
TITLE: “From Bench to Vending Machine: Development and Deployment of Novel Diagnostic testing for SARS-CoV-2 using Genomic Technology”
ABSTRACT: Frequent and widespread testing of members of the population who are asymptomatic for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is essential for the mitigation of the transmission of the virus. Despite the recent increases in testing capacity, tests based on quantitative polymerase chain reaction (qPCR) assays cannot be easily deployed at the scale required for population-wide screening. Here, we show that next-generation sequencing of pooled samples tagged with sample-specific molecular barcodes enables the testing of thousands of nasal or saliva samples for SARS-CoV-2 RNA in a single run without the need for RNA extraction. The assay, which we named SwabSeq, incorporates a synthetic RNA standard that facilitates end-point quantification and the calling of true negatives, and that reduces the requirements for automation, purification and sample-to-sample normalization. We used SwabSeq to perform 80,000 tests, with an analytical sensitivity and specificity comparable to or better than traditional qPCR tests, in less than two months with turnaround times of less than 24 h. SwabSeq could be rapidly adapted for the detection of other pathogens.

https://qcb.ucla.edu/wp-content/uploads/sites/14/2021/07/Valerie-Arboleda-edited.mp4

QCBio Research Seminar in collaboration with B.I.G. Summer: David Wong
2021-07-30 14:00 - 14:30
TITLE: “Salivary exRNA for Gastric Cancer Detection”
ABSTRACT: Biomarkers are needed for non-invasive early detection of gastric cancer (GC). We investigated whether salivary extracellular RNA (exRNA) biomarkers can be used as an efficient and economical clinical evaluation tool for GC. Unstimulated whole saliva samples were prospectively collected from 294 subjects (163 GC and 131 non-GC controls) who underwent endoscopic evaluation at the Samsung Medical Center in Korea. The salivary transcriptomes of 63 GC and 31 non-GC controls were profiled, and mRNA biomarker candidates were verified with RT-qPCR. In parallel, microRNA biomarkers were profiled and verified with saliva samples from 10 GC and 10 controls. Candidate biomarkers were validated with RT-qPCR in an independent cohort of 100/100 saliva samples from GC and non-GC patients. Validated individual markers were configured into a best performance panel. We identified 30 mRNA and 15 miRNA candidates whose expression pattern associated with the presence of gastric cancer. Among them, 12 mRNA and 6 miRNA candidates were verified with the discovery cohort by RT-qPCR and further validated with the independent cohort (n=200). The configured biomarker panel consisted of 3 mRNAs (SPINK7, PPL and SEMA4B) and 2 miRNAs (miR-140-5p and miR-301a), which were all significantly down-regulated in GC group, yielded an AUC of 0.81 (95%CI, 0.72-0.89). When combined with demographic factors, the performance of the panel reached an AUC of 0.87 (95%CI, 0.80-0.93). We have discovered and validated a panel of salivary exRNA biomarkers with credible clinical performance for the detection of GC. Our study demonstrates the credential of salivary exRNA biomarker as a potential screening and risk-assessing tool for GC.
https://qcb.ucla.edu/wp-content/uploads/sites/14/2021/07/David-Wong-edited.mp4

QCBio Research Seminar in collaboration with B.I.G. Summer: Harold Pimentel
2021-07-24 14:00 - 14:30
TITLE: “Model driven design and analysis of quantitative phenotype screens”
ABSTRACT: Increasingly, CRISPR screens are coupled with flow cytometry (FACS) to sort cells and quantify the
impact of genetic perturbations on a continuous phenotype. While FACS provides much more
quantitative information than simple survival screens, it introduces a number of experimental and
statistical challenges. Furthermore, as experimentalists push these screens in limited primary cells
or in vivo, they lack principled guidelines on how experimental parameters including multiplicity of
infection, guide RNA coverage, or FACS bin cutoffs affect statistical power. We present models for
both experimental design and inference of gene regulation in these screens. We show that
commonly used parameters are far from optimal and screens can be performed with a 20 times
reduction in cells at comparable accuracy. Our inference procedure models biological replicates,
infers the latent protein distribution, and infers experimental parameters. Together these analyses
provide a holistic framework for designing and analyzing highly parallel FACS screens.
https://qcb.ucla.edu/wp-content/uploads/sites/14/2021/07/Harold-Pimentel-edited.mp4

QCBio Research Seminar in collaboration with B.I.G. Summer: Hilary Coller
2021-07-16 14:00 - 14:30
TITLE: “Is there a Quiescence Histone Code?”
ABSTRACT: Many of the cells in our bodies are quiescent, that is, temporarily not dividing. Under certain physiological conditions such as during tissue repair and maintenance, quiescent cells receive the appropriate stimulus and are induced to enter the cell cycle. The ability of cells to successfully transition into and out of a quiescent state is crucial for many biological processes including wound healing, stem cell maintenance, and immunological responses. Histone modifications have been shown to play a role in chromatin packing and accessibility, nucleosome mobility, gene expression, and chromosome arrangement. We have been testing the role of the H4K20me3 mark as a regulator of quiescence in cultured cells and in mice. Our data implicate this histone mark in chromatin compaction, cell proliferation, chromosome positioning, expression of critical cell cycle regulatory proteins, and mouse growth during development. Moving forward, our goal is to test whether H4K20me3 is part of a histone code that ensures proper chromosome compaction and positioning to establish and maintain a quiescent state.

QCBio Research Seminar in collaboration with B.I.G. Summer: Paivi Pajukanta
2021-07-09 14:00 - 14:30
TITLE: “Integrating single cell omics and deep phenotype data to discover genes underlying cardiometabolic disorders”
ABSTRACT: Obesity predisposes to cardiometabolic disorders (CMDs), such as type 2 diabetes, multiple dyslipidemias, and non-alcoholic fatty liver disease (NAFLD). We are interested in how cell-type level gene expression contributes to CMDs and impacts cross talk between cardiometabolic tissues. We hypothesized that obesity-induced inflammatory changes in adipose tissue alter the cell-type composition and key functions of this obesity responsive tissue, which drives ectopic deposition of fat into the liver. To this end, we have generated adipose and liver single nucleus RNA-seq reference data sets, and leveraged the cell-type markers identified in these reference data sets to decompose cell-type proportions in bulk adipose tissue and liver RNA-seq cohorts. This decomposition has allowed us to identify which adipose tissue and liver cell-types are associated with human CMDs. Moving forward, our goal is to discover genetic and biological mechanisms underlying CMDs at the single cell resolution.

QCBio Research Seminar in collaboration with B.I.G. Summer: Jingyi Jessica Li
2021-07-02 14:00 - 14:30
TITLE: “Applications of generalized additive models and copulas to single-cell RNAseq computational method development: PseudotimeDE and scDesign2”
ABSTRACT:
Part 1: PseudotimeDE: inference of differential gene expression along cell pseudotime with well-calibrated p-values from single-cell RNA sequencing data
To investigate molecular mechanisms underlying cell state changes, a crucial analysis is to identify differentially expressed (DE) genes along the pseudotime inferred from single-cell RNA-sequencing data. However, existing methods do not account for pseudotime inference uncertainty, and they have either ill-posed p-values or restrictive models. Here we propose PseudotimeDE, a DE gene identification method that adapts to various pseudotime inference methods, accounts for pseudotime inference uncertainty, and outputs well-calibrated p-values. Comprehensive simulations and real-data applications verify that PseudotimeDE outperforms existing methods in false discovery rate control and power.
Part 2: scDesign2: a transparent simulator that generates high-fidelity single-cell gene expression count data with gene correlations captured
A pressing challenge in single-cell transcriptomics is to benchmark experimental protocols and computational methods. A solution is to use computational simulators, but existing simulators cannot simultaneously achieve three goals: preserving genes, capturing gene correlations, and generating any number of cells with varying sequencing depths. To fill this gap, we propose scDesign2, a transparent simulator that achieves all three goals and generates high-fidelity synthetic data for multiple single-cell gene expression count-based technologies. In particular, scDesign2 is advantageous in its transparent use of probabilistic models and its ability to capture gene correlations via copulas.
https://qcb.ucla.edu/wp-content/uploads/sites/14/2021/06/Jessica-Li-7.2.21-edited.mp4

QCBio Research Seminar: Nan (Miles) Xi (Li JJ)
2021-06-04 11:30 - 12:00
TITLE: “DoubletCollection: An R package that integrates cutting-edge computational doublet-detection methods.”
ABSTRACT: The existence of doublets is a key confounder in single-cell RNA sequencing (scRNA-seq) data analysis. There are several computational methods for detecting doublets from scRNA-seq data.
We develop an R package DoubletCollection to integrate the installation and execution of those methods. DoubletCollection also provides a unified interface to perform and visualize downstream analysis after doublet detection.
In this talk, we will introduce a protocol of using DoubletCollection to benchmark doublet-detection methods. This protocol can automatically accommodate new doublet-detection methods and datasets in the fast-growing scRNA-seq field.
https://qcb.ucla.edu/wp-content/uploads/sites/14/2021/05/Nan-Miles-Xi-edited.mp4

QCBio Research Seminar: Amelia Palermo (Graeber)
2021-06-04 11:00 - 11:30
TITLE: “Metabolic dependencies of ecDNA and HSR focal amplification modes and plasticity.”
ABSTRACT: The focal amplification (FA) of genes that support the uncontrolled growth and proliferation of cells (i.e., oncogenes) on homogeneous chromosomal staining regions (HSRs, chromosomal) ans extrachromosomal DNA (ecDNA) is a hallmark of resistant cancers. However, it remains an open question whether oncogene FA is affected by cellular metabolism and by the composition of the tumor microenvironment. This is important because cancers carrying oncogene focal amplifications, particularly on ecDNA, can evolve fast, and are highly malignant and difficult to treat. In this context, our group recently observed high plasticity of ecDNA+/HSR+ BRAF amplification upon combined BRAF plus MEK inhibitor (i.e., vemurafenib plus selumetinib) escalation in an in-house model of resistant melanoma. We profiled this in vitro model by metabolomics and lipidomics analysis, revealing that both FA- vs FA+, and ecDNA+ vs HSR+ cells are characterized by extensive metabolism reprogramming and substantial changes in lipid composition. Ultimately, our observations support the hypothesis that oncogene focal amplification on ecDNA and HSRs can be modulated by leveraging unique metabolic vulnerabilities.

QCBio Academic Jobs - Postdoc Career Development Series: "Starting a New Lab"
2021-06-03 15:00 - 16:00
Panelist: Elaine Hsiao

QCBio Research Seminar: Jakob Von Morgenland (Venugopal)
2021-05-28 11:00 - 11:30
TITLE: “Constructing a Functional Interactome from Published Work to Identify Underrepresented and Integrative Effects of Neuroinflammatory Cytokines on Neural Excitability.”
ABSTRACT: Maintaining normal excitability is a key function of our nervous system which is subject to ongoing perturbations such as aging and chronic neurodegeneration. Neuroinflammatory responses which are widely associated with injury and disease are often disregarded as ongoing modulators of brain excitability. Indeed, neuroinflammatory cytokines such as TNF-α released by resident glial cells in the nervous system can modify ionic conductivity in neurons at nano-molar concentrations at acute and chronic timescales and in turn can mediate emergence of neural dysfunctions observed during disease development. This suggests that understanding how and when cytokines act on neurons could represent targets for therapeutic modulation. Therefore, we set out to examine in existing literature how strong are the evidence for neuroinflammatory modulation of neural excitability. Surprisingly, neither the database search using popular bioinformatics tools such as the STRING, nor the top hits on Pubmed search using keywords such as “cytokine” AND “ion channels” revealed strong evidence for molecular interactions between inflammatory cytokines in the brain and voltage-gated ion channel proteins responsible for neural signaling. However, a more detailed examination of the literature uncovered a few yet convincing mechanistic studies demonstrating that cytokines can induce changes in ionic conductivity, ion channel protein expression as well as action potential frequencies. Driven by these findings, we set out to develop a novel functional interaction score (FIS) to quantitate the strength of evidence for cytokine actions on neural excitability. We then used such scores to generate a protein-protein interactome to enable further application of graph theory-based approaches to analyze the functional links between neuroinflammation and neural excitability. Our analysis and novel scoring also revealed 1-to-N associations between cytokines and ion channel proteins. In my talk, I will discuss this journey and also share our ongoing innovative approach using the cytokine-ion channel associations in dynamic neuron models as predictive tools to test integrative actions of cytokines on neuronal excitability.

QCBio Research Seminar: Yi Ding (Pasaniuc)
2021-05-28 11:00 - 11:30
TITLE: “Large uncertainty in individual PRS estimation impacts PRS-based risk stratification.”
ABSTRACT: Large-scale genome-wide association studies have enabled polygenic risk scores (PRS), which estimate the genetic value of an individual for a given trait. Since PRS accuracy is typically assessed using cohort-level metrics, uncertainty in PRS estimates at individual level remains underexplored. In this talk, we will first introduce a Bayesian framework that can estimate the variance of an individual’s PRS and can yield well-calibrated credible intervals for the genetic value of a single individual. Then we will discuss the impact of PRS uncertainty on risk stratification and present a probabilistic PRS-based risk stratification approach to incorporate the uncertainty in individual PRS estimates. Finally, we’ll present a theoretical estimate of individual PRS variance as a function of heritability, number of causal SNPs and sample size.
https://qcb.ucla.edu/wp-content/uploads/sites/14/2021/05/Yi-Ding-edited.mp4

QCBio Academic Jobs - Postdoc Career Development Series: "Demystifying the Publication Process in a High Profile Journal"
2021-05-27 15:00 - 16:00
Panelist: Emilie Marcus
https://qcb.ucla.edu/wp-content/uploads/sites/14/2021/03/Emilie-Marcus.mp4

Bioinformatics/Human Genetics Seminar Series: Raluca Gordân, PhD
2021-05-24 11:00 - 12:00
Associate Professor, Biostatistics & Bioinformatics, Center for Genomic and Computational Biology, Duke University
“TBD”
Hosted by Jason Ernst

QCBio Research Seminar: Shamus Cooley (Deeds)
2021-05-21 11:30 - 12:00
TITLE: “Unbiased analysis of single cell RNA sequencing data reveals previously uncharacterized heterogeneity in small cell lung cancer cell lines.”
ABSTRACT: Small Cell Lung Cancer (SCLC) accounts for approximately 13% of all new lung cancer diagnoses. SCLC exhibits propensity for early metastasis, rapid cell division, high levels of replication stress, the ability to cope with certain oxidative and metabolic stresses, and evasion of apoptosis and the effector cells of the immune system. Together, these factors contribute to an exceedingly poor prognosis with patient survival measured in months, not years, that has led to a recalcitrant cancer designation for SCLC by the National Cancer Institute. Nevertheless, systemic therapies that include immunotherapy are beginning to show promise in the clinic. Although, these results are encouraging, many patients do not respond to, or rapidly recur after, current regimens, necessitating alternative or complementary therapeutic strategies. Heterogeneity of cancer cells is a key factor by which tumors resist treatment, and It is increasingly appreciated that there are discrete molecular subtypes of SCLC that can differ in their response to different therapies. In my talk, I will describe how we use gene expression data obtained from single-cell RNA sequencing of eight immortalized SCLC cell lines to characterize heterogeneity in SCLC. I will show that, in addition to established classification of cancer sub-types, there is an orthogonal axis of heterogeneity in which exist distinct subpopulations, each with its own unique gene expression profile. One such subpopulation is characterized by stem-like properties and decreased expression of key signaling proteins. This finding suggests that SCLC tumors are highly heterogeneous in make-up, and that consideration of this stem-like subpopulation will be critical for the development of effective therapeutics.
https://qcb.ucla.edu/wp-content/uploads/sites/14/2021/04/Shamus-Cooley-edited.mp4

QCBio Research Seminar: Olga Schubert (Kruglyak)
2021-05-21 11:00 - 11:30
TITLE: “Genome-wide survey of mutations influencing protein abundances in yeast”
ABSTRACT: Our understanding of how protein-level regulation is encoded in the genome and how protein abundances are affected by DNA sequence variation remains sparse. I will discuss our genetic screen based on large-scale pooled base editing that allows us to capture the effects of thousands of mutations on the abundance of individual proteins in yeast. We applied this screen to 11 proteins and gained new insights into the components, scale and connectedness of genetic networks underlying the regulation of protein abundances.
https://qcb.ucla.edu/wp-content/uploads/sites/14/2021/03/Olga-Schubert-edited.mp4

QCBio Academic Jobs - Postdoc Career Development Series: "Research Statement"
2021-05-20 15:00 - 16:00
Panelist: Paul Boutros
https://qcb.ucla.edu/wp-content/uploads/sites/14/2021/03/Paul-Boutros-edited.mp4

Bioinformatics/Human Genetics Seminar Series: Viktor Adalsteinsson, PhD
2021-05-17 11:00 - 12:00
Associate director, Gerstner Center for Cancer Diagnostics, Broad Institute
“Ultrasensitive detection of minimal residual disease”
Hosted by Jasmine Zhou

QCBio Research Seminar: Rina Ding (Hsu)
2021-05-14 11:00 - 12:00
TITLE: “Multimodal radiomic analysis of biparametric MRI to predict biochemical recurrence after radical prostatectomy.”
ABSTRACT: Integration of information across multiple modalities and biological scales has the potential to improve the prediction of disease outcomes and response to treatments. In this talk, I will discuss our ongoing work to predict prostate cancer aggressiveness by combining information from biparametric MRI. We predict biochemical recurrence (BCR) in 343 men post radical prostatectomy by fusing quantitative image features extracted from T2- and diffusion-weighted scans. We found the fused features improved the prediction of BCR when compared to various baseline models and clinical assessments. In the future, we intend to incorporate genomic data, relating imaging phenotypes to underlying tumor biology.
https://qcb.ucla.edu/wp-content/uploads/sites/14/2021/05/Rina-Ding-edited.mp4

QCBio Research Seminar: Brian Orcutt-Jahns (Meyer)
2021-05-14 11:00 - 11:30
TITLE: “A simple, two-step, multivalent binding model predicts IL-2 mutein cell signaling profiles.”
ABSTRACT: The common γ-chain cytokines are promising immune therapies, but have been limited in their efficacy due to their induction of non-specific immune activation. Here, we visualized immune cell response to both mono- and multivalent γ-chain muteins using a structured dimensionality reduction scheme. We then used a simple multivalent binding model to predict cell type-specific signaling with high accuracy. Finally, we use this model to generate guidelines for engineering more effective γ-chain therapeutics.
https://qcb.ucla.edu/wp-content/uploads/sites/14/2021/03/Brian-Orcutt-Jahns-edited.mp4

QCBio Academic Jobs - Postdoc Career Development Series: "Chalk Talk & Negotiating Academic Jobs"
2021-05-13 15:00 - 16:00
Panelist: Leonid Kruglyak

Bioinformatics/Human Genetics Seminar Series: Alexandra Stern, PhD
2021-05-10 11:00 - 12:00
Associate Dean for the Humanities, University of Michigan-Ann Arbor
“TBD: History of genetic counseling”
Hosted by Christina Palmer

QCBio Research Seminar: Ruochen Jiang (Li JJ)
2021-05-07 11:30 - 12:00
TITLE: “Sources of zeros in single-cell RNA-seq data and how they affect data analysis.”
ABSTRACT: Single-cell RNA sequencing (scRNA-seq) technologies have revolutionized biomedical sciences by enabling genome-wide profiling of gene expression levels at an unprecedented single-cell resolution. A distinct characteristic of scRNA-seq data is the vast proportion of zeros unseen in bulk RNA-seq data. Researchers view these zeros differently: some regard zeros as biological signals representing no or low gene expression, while others regard zeros as false signals or missing data to be corrected. As a result, the scRNA-seq field faces much controversy regarding how to handle zeros in data analysis. In this paper, we first discuss the sources of biological and non-biological zeros in scRNA-seq data. Second, we summarize the advantages, disadvantages, and suitable users of three input data types: original counts, imputed counts, and binarized counts. Third, we evaluate the impacts of non-biological zeros on cell clustering and differential gene expression analysis. Finally, we discuss the open questions regarding non-biological zeros, the need for benchmarking, and the importance of transparent analysis.
https://qcb.ucla.edu/wp-content/uploads/sites/14/2021/04/Ruochen-Jiang-edited.mp4

QCBio Research Seminar: Erin Molloy (Sankararaman)
2021-05-07 11:00 - 11:30
TITLE: “Advancing admixture graph estimation via maximum likelihood network orientation.”
ABSTRACT: Admixture, the interbreeding between previously distinct populations, is a pervasive force in evolution. The evolutionary history of populations in the presence of admixture can be modeled by augmenting phylogenetic trees with additional nodes that represent admixture events. However, these admixture graphs present formidable inferential challenges. Exhaustively evaluating all admixture graphs can be prohibitively expensive, so heuristics have been developed to enable efficient search. One heuristic, implemented in the popular method TreeMix, consists of adding edges to a starting tree while optimizing a suitable objective function. In this talk, we will present a demographic model (with one admixed population incident to a leaf) where TreeMix and any other starting-tree-based maximum likelihood heuristic using its likelihood function is guaranteed to get stuck in a local optimum and return an incorrect network topology. We will then demonstrate how this issue can be addressed using our new search strategy: maximum likelihood network orientation (MLNO).
https://qcb.ucla.edu/wp-content/uploads/sites/14/2021/04/Erin-Molloy-edited.mp4

QCBio Academic Jobs - Postdoc Career Development Series: "Job Talk"
2021-05-06 15:00 - 16:00
Panelist: Kirk Lohmueller
https://qcb.ucla.edu/wp-content/uploads/sites/14/2021/03/Kirk-Lohmueller-edited.mp4

Bioinformatics/Human Genetics Seminar Series: Aaron Panofsky, PhD
2021-05-03 11:00 - 12:00
Associate Professor and Vice Chair of Academic Personnel, UCLA Institute for Society and Genetics
“Citizen Scientific Racism: White Nationalist Appropriations of Genetic Research”
Hosted by Christina Palmer

QCBio Research Seminar: Alexis Weber (Geschwind & de la Torre-Ubieta)
2021-04-30 11:30 - 12:00
TITLE: “Defining chromatin accessibility and molecular dysregulation in Down Syndrome.”
ABSTRACT: Despite accumulating almost two centuries of medical information, the exact mechanisms underlying Down Syndrome (DS) developmental pathology remain unknown. DS is caused by trisomy of chromosome21 (T21), but without pinpointing the way in which T21 confers molecular dysfunctions and subsequently impairs neurodevelopment, it has been difficult to devise medical interventions that will reduce cognitive deficits. In order to identify these mechanisms in DS and deconvolute the inherent complexity of the developing brain, we are leveraging single cell technologies to contrast DS and healthy expression profiles and chromatin accessibility in midgestation brain tissue and patient-derived primary human neural progenitor cells (phNPCs). Based on previous bulk RNA and chromatin analyses in DS samples and our preliminary data, we anticipate 1) changes in cell composition and 2) altered gene-regulatory networks affecting neurogenesis pathways in neural progenitors, oligodendrocyte precursor cells, and astrocytes. By uncovering these cytological and molecular aberrations, we hope to progress the understanding of neurodevelopment and DS to promote medical advances in the future.
https://qcb.ucla.edu/wp-content/uploads/sites/14/2021/03/Alexis-Weber-edited-1.mp4

QCBio Research Seminar: Ashfaq Ahmed (Venugopal)
2021-04-30 11:00 - 11:30
TITLE: “Mechanisms of robust entrainment of biological oscillators involved in gastric peristalsis.”
ABSTRACT: Oscillator entrainment is a widely observed phenomenon in natural systems. Using a computational modeling approach, we decipher the essential intrinsic and extrinsic mechanisms of robust entrainment of biological oscillators involved in gastric peristalsis. Specifically, we show that the constitutive intercellular IP3-facilitated pacemaker pathway in these cells stabilizes cellular frequencies, extends longitudinal entrainment range, and enables rostro-caudal spread of a gastric slow-wave in a realistic multi-cellular coupled network. Our comprehensive model and the novel predictions offer directions for future experiments and theoretical work.
https://qcb.ucla.edu/wp-content/uploads/sites/14/2021/04/Ashfaq-Ahmed-edited.mp4

QCBio Academic Jobs - Postdoc Career Development Series: "The Holistic Job Packet"
2021-04-29 15:00 - 16:00
Panelist: Roy Wollman

Bioinformatics/Human Genetics Seminar Series: Jennifer E. Phillips-Cremins, PhD
2021-04-26 11:00 - 12:00
Assistant Professor of Bioengineering, University of Pennsylvania
“Genome folding, unfolding, and refolding in the mammalian brain”
Hosted by Hilary Coller

Townhall on Diversity, Equity & Inclusion
2021-04-23 11:00 - 12:00
