genomicsatjhu-logoThe Genomics@JHU Seminar Series brings top genomics investigators from outside the University to present the latest research in Genomics. G@JHU is sponsored by the Institute for Data Intensive Engineering and Science (IDIES), the Department of Computer Science, and the Department of Biostatistics.

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Past Seminars

Decoding epigenetic programs in cellular differentiation and T cell dysfunction in tumors

  • Where: BSPH E2030 (Feinstone)
  • When: May 15, 2017, 13:30
  • Christina Leslie
  • A Genomics@JHU Seminar

Abstract: Dysregulated epigenetic developmental programs are a feature of many cancers, and the diverse differentiation states of immune cells as well as their dysfunctional states in tumors are in part epigenetically encoded. We developed an integrative computational strategy to exploit genome-wide data on chromatin accessibility (DNase-seq or ATAC-seq), histone modifications (ChIP-seq), and transcription (RNA-seq) in … Continued

Data-driven re-annotation of patient tumors and derived model systems

  • Where: BSPH E3609 (Genome Café)
  • When: May 01, 2017, 13:30
  • Benjamin Haibe-Kains
  • A Genomics@JHU Seminar

Abstract: The success of precision medicine largely relies on comprehensive characterization of patient tumors and their derived model systems to select the best therapy for each individual patient. Recent initiatives generated massive amounts of molecular data for healthy (GTEx) and tumor (TCGA) tissues from patients, as well as patient-derived cancer cell lines (Cancer Cell Line … Continued

What can we learn from human genomics at scale and how do we get there?

  • Where: BSPH E3609 (Genome Café)
  • When: April 03, 2017, 13:30
  • Joe Pickrell
  • A Genomics@JHU Seminar

Abstract: A primary goal of human genetics is to understand the genetic causes of phenotypic variation. Recent successes in genome-wide association studies have shown that achieving this goal requires collecting and analyzing data at scale. I will discuss projects that center around this thesis. First, I will discuss analyses of the genetics of lifespan in … Continued

Diffusion-based Interactions in Noisy Single Cell Data

  • Where: Charles Commons conference center
  • When: November 14, 2016, 13:30
  • Smita Krishnaswamy
  • A Genomics@JHU Seminar

Abstract Recently, there have been significant advances in single-cell genomic and proteomic technologies that can measure the expression of thousands of mRNA transcripts and dozens of proteins. However, this data suffers from sparsity and noise. Furthermore, its high dimensionality makes interpreting the data difficult for biologists. Our aim is to facilitate interpretation by providing a … Continued

Tumor neoepitope selection for biomarker discovery and therapeutic vaccination

  • Where: Barber Conference Room at Charles Commons, 10 E 33rd St. Baltimore, MD
  • When: October 24, 2016, 13:30
  • Jeff Hammerbacher
  • A Genomics@JHU Seminar

Abstract We’ll review some open source software our lab has developed to facilitate a Phase I clinical trial of a personalized therapeutic vaccine targeting tumor neoepitopes. We’ll also present some results from our analysis of clinical trials of checkpoint blockade in 3 different cancer types and some open source software we’ve created to facilitate similar … Continued

The Impact of Genetic Variation on Gene Regulation from RNA to Protein in Humans

  • Where: Barber Conference Room at Charles Commons, 10 E 33rd St. Baltimore, MD
  • When: October 17, 2016, 13:30
  • Zia Khan of UMCP
  • A Genomics@JHU Seminar

Abstract Understanding how genotype and environment interact to impact phenotypic variation is a central goal of genetics. Studies of important phenotypes in humans such as disease risk and drug toxicity have identified genomic regions and variants of interest. Yet, in many cases, the mechanisms by which these variants act are less clear. Gaining a better … Continued

Likelihood Approaches to Structural Variant Discovery: From Integrating Signals in Individual Genomes Towards Simultaneous Variant Discovery in Populations

  • Where: Bloomberg School of Public Health
  • When: April 26, 2016, 10:30
  • Suzanne Sindi
  • A Genomics@JHU Seminar

Abstract Structural variants (SVs) – such as deletions, insertions, copy-number gains and inversions – are rearrangements of a region of DNA relative to a reference. Until relatively recently, SVs were thought to be rare in genomes of healthy individuals, especially mammals. However, advances in high-throughput DNA sequencing, combined with the availability of high-quality reference genomes, … Continued

Fast Algorithms for Improved Transcriptome Analysis

  • Where: Bloomberg School of Public Health
  • When: April 05, 2016, 10:30
  • Rob Patro of Stony Brook University
  • A Genomics@JHU Seminar

Abstract Short read alignments are the lingua franca in much of computational genomics. Most analyses “begin with a bam”. This requires that the reads are aligned to the reference (genome or transcriptome) of interest. Given the tremendous speed of acquisition of sequencing data, the process of alignment can pose a significant computational burden. Crucially, this … Continued

Selecting genomics assays and making sense of the resulting data

  • Where: Welsh Library West Reading Room, 1900 E. Monument St
  • When: February 23, 2016, 10:00
  • William Noble of the University of Washington
  • A Genomics@JHU Seminar

Abstract Genomic sequencing assays such as ChIP-seq and DNase-seq can measure a wide variety of types of genomic activity, but the high cost of sequencing limits the number of these assays that are usually performed in a given experimental condition. I will discuss a principled method for selecting which genomics assays to perform, given a … Continued

(Data-driven) Strategies to Predict Intra- and Inter-cellular Signaling Dynamics and Function

  • Where: Barber Conference Room at Charles Commons, 10 E 33rd St. Baltimore, MD
  • When: December 08, 2015, 10:00
  • Neda Bagheri of Northwestern University
  • A Genomics@JHU Seminar

Abstract In the past decade, emerging technologies have offered increasingly high throughput data with greater resolution to investigate cellular responses. To gain insight from dynamic gene expression, transcription factor activity, phospho-signaling or other data, improved computational strategies to analyze, integrate, and predict complex biological function must be developed. We employ a variety of inference and … Continued