The paper of Haiyi and Minxue entitled “COEM: Cross-Modal Embedding for MetaCell Identification” was selected for a spotlight talk at the Computational Biology Workshop in the 39th International Conference on Machine Learning (ICML 2022) to be held in Baltimore, MD in July 22, 2022. Congratulations…
Robert presented his work on COPD subtyping at the American Thoracic Society (ATS) 2022 meeting. Congratulations Robert! …
Takis gave an invited talk and met with colleagues at the Department of Biomedical Engineering at the University of Virginia, Charlottesville. The title of the talk was “Multi-scale Data Integration and Causal Inference for Medical Research”. …
Congratulations to Tyler for the acceptance by Patterns of the paper “Essential Regression – a generalizable framework for inferring causal latent factors from multi-omic datasets“, which he is first co-author. The paper describes a new method to develop predictive causal models in high-dimensional, highly collinear data. A pre-print of this paper…
Tyler Lovelace, a CPCB PhD student in our group, was awarded an NIH F31 Predoctoral Fellowship from the National Library of Medicine (NLM). The F31 award is entitled “Causal graphical methods for high-dimensional heterogeneous biomedical data“. We are very proud of Tyler who got this highly…
In the first in-person computational biology conference, ROCKY 2021, Takis made an oral and poster presentation regarding the work of former PhD student, Kristina Buschur, on COPD subtyping. ROCKY conference was held in Snowmass, CO and followed all COVID guidances, requiring attendees to either show proof of vaccination or subjected…
Congratulations to Feng (co-advised; primary advisor: Dario Vignali) for the acceptance by Cell Reports Medicine of the paper he co-authored “Critically ill COVID-19 patients 1 exhibit peripheral immune profiles predictive of mortality and reflective of SARS-CoV-2 viral burden in the lung“. The paper describes the results of analysis of single cell…
After nearly 20 years since its beginning our Lab put together its first NewsLetter! The last 2 years were challenging and full of events. From the BLM movement to elections and let’s not forget this “other thing”. The Lab stayed isolated but still productive. This first Newsletter serves as…
The Benos Lab received an R01 grant from NHLBI-NIH to develop interpretable probabilistic graphical models for multi-modal datasets. The methods will be used to identify factors causally linked to the progression of chronic obstructive pulmonary disease (COPD). COPD is the 3rd leading cause of death worldwide [1]. In 2019,…
The Benos Lab received an R01 grant from NHLBI-NIH to develop machine learning methods to identify and study chronic obstructive pulmonary disease (COPD) subtypes. COPD is the 3rd leading cause of death worldwide [1]. In 2019, WHO estimated that 3.23 million people died for COPD [2]. More than 140,000…
