Tag Archives: seminars

YINS Fwd: Google: Yale PhD, Postdoc Lunch, Oct 12, 12pm – 1pm

Subject: Google: Yale PhD, Postdoc Lunch, Oct 12, 12pm – 1pm

Please share with interested Yale PhDs and Postdocs.

Interested in learning more about the cool projects happening within engineering at Google? Join us for lunch and product talks from Googlers working on a variety of awesome teams, including Google Assistant, Google Lens, Daydream (VR/AR), and others. Please be sure to RSVP here [https://goo.gl/NaWBrV]

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