Tag Archives: seminars

YSPH Biostatistics Seminar on October 10

We invite you to attend the YSPH Biostatistics Seminar on Tuesday, October 10, 2017.

Patrick Flaherty will be the guest speaker.

Title: “A Nonparametric Bayesian Model for Single-cell Variant Calling”

Date: Tuesday, October 10, 2017

Time: 12:00 pm – 1:15 pm seminar

Place: LEPH 115

Laboratory of Epidemiology and Public Health

60 College Street

Yale calendar Link: YSPH Biostatistics Seminar: "A Nonparametric Bayesian Model for Single-cell Variant Calling"

Yale/NIDA Neuroproteomics Center Research in Progress Meeting Friday (10/6) at 12:30 PM

Reminder that our next Research in Progress Meeting is this Friday, October 6, 2017 from 12:30 – 1:30 PM in SHM Room C428, at 333 Cedar St. The two speakers will be:

Dr. Marina Picciotto, Charles B. G. Murphy Professor of Psychiatry and Professor in the Child Study Center, of Neuroscience and of
Pharmacology, Yale University; who will present, “A Systematic Evaluation of High-affinity α4β2 Nicotinic Acetylcholine Receptor Phosphorylation” and

Dr. Mary M. Torregrossa, Assistant Professor of Psychiatry, University of Pittsburgh; who will present, “Identification of Novel Regulators of Memory Extinction and Reconsolidation Using Phosphoproteomics”

We urge all Yale and if reasonable, non-Yale members of the Center and interested researchers to please attend this important Neuroproteomics Center event! We ask principal investigators to please post the attached seminar announcement and circulate it to all members of their laboratories. Please reply if you would like to add or delete names from our Center’s email address listing.

Pizza will be served at 12:15 PM. All are welcome!!
100617_Neuroproteomics Center Seminar Notice_081517.pdf

Two CBB events: Rafael Irizarry, Computational Biology and Bioinformatics speaker on 10-4-17

Dr. Rafael Irizarry from Harvard University will be the guest speaker.

Title: “Overcoming Bias and Batch Effects in single cell and bulk RNAseq Data”

Date: Wednesday, October 4, 2017

Time: 4:00 seminar 5:00 refreshments

Place: BML Auditorium, 310 Cedar Street

Hosted by: Steven Kleinstein, PhD

Flyer is attached for your review.

cbb_seminar_series_Oct.doc.pdf

Biostatistics Seminar: 9/26/17 – 12:00 Noon – LEPH 115

https://medicine.yale.edu/events/ysph.aspx?from=2017-09-26&to=2017-10-03#single-event_9691

Good morning,

Please join the Biostatistics Seminar scheduled for Tuesday, September 26, 2017 at 12:00 Noon in LEPH 115.

Yale calendar Link: YSPH Biostatistics Seminar: “Constructing Tumor-Specific Gene Regulatory Networks Based on Samples with Tumor Purity Heterogeneity”

Thank you,

Speaker: Pei Wang, PhD

Institution: Icahn School of Medicine at Mount Sinai

Time & Place: 12:00 Noon in LEPH 115, 60 College St.

11:45 AM Lunch in LEPH 108

Title: “Constructing Tumor-Specific Gene Regulatory Networks Based on Samples with Tumor Purity Heterogeneity”

Abstract:

Tumor tissue samples often contain an unknown fraction of normal cells. This problem well known as tumor purity heterogeneity (TPH) was recently recognized as a severe issue in omics studies. Specifically, if TPH is ignored when inferring co-expression networks, edges are likely to be estimated among genes with mean shift between normal and tumor cells rather than among gene pairs interacting with each other in tumor cells. To address this issue, we propose TSNet a new method which constructs tumor-cell specific gene/protein co-expression networks based on gene/protein expression profiles of tumor tissues. TSNet treats the observed expression profile as a mixture of expressions from different cell types and explicitly models tumor purity percentage in each tumor sample. The advantage of TSNet over existing methods ignoring TPH is illustrated through extensive simulation examples. We then apply TSNet to estimate tumor specific co-expression networks based on breast cancer expression profiles. We identify novel co-expression modules and hub structure specific to tumor cells.
BIS Seminar Notice Sept 26_2017.pdf

Yale Systems Biology Institute – Seminar Series, Michael Miller, PhD Sept 26th @ 12:00pm West Campus

Please join us for the Yale Systems Biology Institute seminar on September 26th at 12:00 p.m., presented by Michael I. Miller, PhD of Johns Hopkins University.

MICHAEL I. MILLER, PhD

Director of Department of Biomedical Engineering and Director of the Center for Imaging Science in the Whiting School of Engineering

Johns Hopkins University

Talk Title: Computational Anatomy and Diffeomorphometry: A Dynamical Systems Model of Neuroanatomy in the Soft Condensed Matter Continuum

Tuesday, September 26

12:00 p.m.

Yale West Campus Conference Center, Room 218

Lunch will be provided
26SEPT2017 – Michael Miller SBI Seminar.pdf V2.pdf

partnership opportunities for the RSG/DREAM 2017 conference in NYC

The International Society of Computational Biology is hosting the 10th Annual ISCB/RECOMB Regulatory and Systems Genomics with DREAM Challenges (RSG/DREAM 2017) on November 19-21 at Memorial Sloan Kettering Cancer Center (MSKCC) in New York City. …

Details about the conference can be seen here:
https://www.iscb.org/recomb-regsysgen2017

Statseminars Applied Data Science Seminar, Speaker: Harlan M Krumholz, MD, SM, September 18th, 4:15pm – 5:30pm

Applied Data Science Seminar

Monday, September 18th, 4:15 PM

Yale Institute for Network Science, 17 Hillhouse Avenue, 3rd Floor

Harlan M Krumholz, MD, SM

Harlan Krumholz is a cardiologist and health care researcher at Yale University and Yale-New Haven Hospital. He received a BS from Yale, an MD from Harvard Medical School, and a Masters in Health Policy and Management from the Harvard University School of Public Health. He is the Harold H. Hines, Jr. Professor of Medicine and Director of the Yale Center for Outcomes Research and Evaluation (CORE), one of the nation’s first and most productive research units dedicated to producing innovations to improve patient outcomes and promote better population health. He is also a Director of the Robert Wood Johnson Foundation Clinical Scholars Program, which prepares talented physicians to become future health care leaders.

Dr. Krumholz has been honored by membership in the Institute of Medicine, the Association of American Physicians, and the American Society for Clinical Investigation. He was named a Distinguished Scientist of the American Heart Association. He was elected to the Board of Trustees of the American College of Cardiology and the Board of Directors of the American Board of Internal Medicine, and was appointed by the U.S. government to the Board of Governors of the Patient-Centered Outcomes Research Institute. He is a 2014 recipient of the Friendship Award from the People’s Republic of China in recognition of his collaborative efforts to develop a national cardiovascular research network.

Dr. Krumholz is the editor of Circulation: Cardiovascular Quality and Outcomes, and editor of CardioExchange, a social media site of the publisher of the New England Journal of Medicine. He has published more than 800 articles and is the author of two books, one on smoking cessation and another on reducing the risk of heart disease. He has a regular blog on Forbes.com and has contributed to the New York Times Wellness blog, the New York Times op-ed page, and National Public Radio Shots blog.

Title: Data Science and Medicine: Where’s the Sweet Spot? Opportunities,

Challenges and Lessons Learned

Abstract: Medicine seems last to the data science party. Despite the immense information needs within medicine and the recent digital transformation of medical data, health care remains far too anchored in a paper-based culture and too infrequently leverages the
possibilities of data science. Yet, we are on the cusp of a
transformative change in health care, one that will push the centrality of the patients’ needs, the importance of the individual over the average, the integrative understanding of biology, behavior, context and environment, the agency of people over their health and health care decision, and the systematic learning from daily of collective experience over the pre-eminence of individual expertise. And we are about to spread expertise instead of sequestering it. In this talk I will examine the possibilities ahead for the application of data science in medicine, with aspirations for a better future.