Recent News

Yoked Learning Work Published in Artificial Intelligence in the Life Sciences

December 3, 2023

We are happy to share that our work on yoked learning for molecular data science has now been published in Artificial Intelligence in the Life Sciences: https://www.sciencedirect.com/science/article/pii/S266

DeepDelta Work Published in Journal of Cheminformatics

October 27, 2023

Our DeepDelta work is now published in Journal of Cheminformatics, thank you to the excellent peer reviewers and everybody that has helped to make this manuscript better.

Presenting at BMES

October 11, 2023

We are excited to present in full force for the 2023 BMES meeting. Details of talks and poster shown below:  

Welcome Chinmay

September 28, 2023

We are thrilled to welcome another post-doctorial associate Chinmay Potnis! He recently recieved his PhD in Chemistry from the University of Louisville and we are excited to see what exciting discoveries here will make here.

New Paper on Design of Coatings for Enzymatically-Controlled Drug Release

September 25, 2023

Thrilled to see this work in print! Huge kudos to Natsuda Navamajiti for inventing bioinformatics-driven design of coatings for pancreatin-dependent drug release.

Check Out Our Review on Artificial Intelligence for Natural Product Drug Discovery

September 12, 2023

We happy to share a new review in Nature Reviews Drug Discovery: [

New Preprint on Yoked Learning

August 16, 2023

We are happy to share a new preprint on Yoked learning for molecular data science: https://chemrxiv.org/engage/api-gateway/chemrxiv/a

Presenting at ACS 2023

August 15, 2023

Daniel gave 2 contributed talks and 1 invited talk at the Fall 2023 ACS National Meeting. Details shown below:

Study Identifying Protein Predictive of Cardiac Complications Following Surgery

August 8, 2023

We are happy to share a new paper that identified Angiopoietin-2 levels are predictive of capillary leak and subsequent edema formation following cardiac surgery. This was a great collaboration with Harvard Medical School and the University of Freiburg.

Paper Published in JCIM

July 28, 2023

This Interpretable Molecular Property Predictions Using Marginalized Graph Kernels work is now published in JCIM, thank you to the excellent peer reviewers and everybody that has helped to make this manuscript better. Congratulations Yan et al! 

NIH MIRA R35 Grant 2023

July 26, 2023

Thank you for the support NIH's National Institute of General Medical Sciences (NIGMS)! We are excited for this major grant to help us develop innovative machine learning learning approaches to create novel drug delivery solutions.

Presenting at CADD GRC

July 21, 2023

Daniel presented "Novel Active Learning Strategies for Preclinical Research" at the Computer Aided Drug Design (CADD) Gordon Research Conference (GRC). A great opportunity to connect with others researching machine learning for drug design. 

Paper Published in Digital Discovery

July 6, 2023

Our paper "Improving molecular machine learning through adaptive subsampling with active learning" has been published and is open access in Digital Discovery. Congrats to Holly Wen and the whole team on this work!

Welcome Lauren

July 3, 2023

We are very excited to welcome our sixth PhD student Lauren! We are looking forward to all of your future exciting discoveries. 

Congrats Chloe on T32 Pharmacological Sciences Training Program Fellowship

June 16, 2023

Congratulations to Chloe on becoming a T32 Pharmacological Sciences Training Program Fellow. This program provides two years of funding and valuable tranining and connections for students in the pharmacological sciences field.

Presenting at the Computational & Systems Biology Annual Symposium

June 13, 2023

Daniel presented "Molecular Machine Learning for Drug Discovery, Delivery, and the Microbiome" at the Computational & Systems Biology Annual Symposium at Colorado State University.

Second Place Group Presentation for BME Retreat

May 18, 2023

We had a great time making a fun video to explain our group's research for the biomedical engineering departmental retreat and recieved second place based on popular vote. Looking forward to enjoying our lunch party reward and doing it again next year!

Congrats to Graduate Ashley

May 14, 2023

Congrats to Ashley for graduating with her B.S. in Computer Science! We are looking forward to hearing about all your future successes.

Congrats Brian on College Acceptances and Attending Princeton

May 1, 2023

Out of many college acceptances, Brian has decided to attend Princeton for his undergrad. We wish you the best of luck and know you will do great things!

New Preprint on Predicting Changes of Molecular Derivatives

April 11, 2023

New preprint from the lab:  “DeepDelta: Predicting Pharmacokinetic Improvements of Molecular Derivatives with Deep Learning”

NIH NIBIB Trailblazer Grant 2023

March 31, 2023

First NIH NOA for our lab, thank you for the support NIH's National Institute of Biomedical Imaging and Bioengineering! .

Welcome Jung!

March 22, 2023

We are happy to welcome Jung, a new research resident, to the lab. Looking forward to the exciting research you will do!

Presenting at the Molecular Engineering & Sciences Institute

March 7, 2023

Daniel presented "Predicting and Improving ADMET Properties of Medications with Machine Learning" at the Molecular Engineering & Sciences Institute at the University of Washington.

New Preprint on Marginalized Graph Kernels

February 20, 2023

New preprint alert from our lab! “Interpretable Molecular Property Predictions Using Marginalized Graph Kernels” https://chemrxiv.org/engage/chemrxiv/article-details/63ef9e761d2d184063a...  

New Preprint on Active Learning Subsampling

February 15, 2023

New preprint alert from our lab! “Improving Molecular Machine Learning Through Adaptive Subsampling with Active Learning” https://doi.org/10.26434/chemrxiv-2023-h8905  

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