Carnegie Mellon University
School of Computer Science  ›  Ray and Stephanie Lane Computational Biology Department  ›  People  ›  Ziv Bar-Joseph

 Ziv Bar-Joseph

FORE Systems Professor of Computer Science, Ray & Stephanie Lane Computational Biology Department, Machine Learning Department

Address:

Ray and Stephanie Lane Computational Biology Department, SCS
Carnegie Mellon University
5000 Forbes Avenue
Pittsburgh, PA 15213
Work Phone: 412-268-8595

Email

Administrative Assistant: Ally Ricarte

Dr. Bar-Joseph’s work focuses on the analysis and integration of static and temporal high throughput biological data for systems biology. Based primarily on methods from machine learning, his group develops computational solutions to problems ranging from experimental design to data analysis, pattern recognition and the reconstruction of dynamic biological networks. Bar-Joseph is currently leading a large center, part of the HuBMAP NIH consortium, focused on developing computational methods to help build a detailed 3D map of the human body. He has also worked on improving algorithms for distributed computational networks by relying on our increased understanding of how biological systems operate and what makes them robust and adaptable.

Lab Members

 
Sean Donahue
Research Programmer
 
Euxhen Hasanaj
Ph.D. Student
 
Matt Ruffalo
Systems Scientist 

Highlighted Publications

Q. Song, J. Wang and Z. Bar-Joseph scSTEM: clustering pseudotime ordered single-cell data
Genome Biology. , 23, 150 2022

E. Hasanaj, J. Wang, A. Sarathi, J. Ding and Z. Bar-Joseph Interactive single-cell data analysis using Cellar Nature Communications. , 13 (1), 1-6, 2022


J. Lugo-Martinez, S. Xu, J. Levesque, D. Gallagher, L.A. Parker, J. Neu, C.J. Stewart, J. E. Berrington, N.D. Embleton, G. Young, K.E. Gregory, M. Good, A. Tandon, D. Genetti, T. Warren, Z. Bar-Joseph. Integrating longitudinal clinical and microbiome data to predict growth faltering in preterm infants  Journal of Biomedical Informatics , in press, 2022

D. Li, J. Ding, Z, Bar-Joseph Unsupervised cell functional annotation for single-cell RNA-seq
Genome Research, in press, 2022. Previous version in Proceedings of the 26th Annual International Conference on Research in Computational Molecular Biology (RECOMB) , pages 349-352, 2022

D. Li, J.J. Velazquez, J. Ding, J. Hislop, M.R. Ebrahimkhani, Z, Bar-Joseph TraSig: inferring cell-cell interactions from pseudotime ordering of scRNA-Seq data Genome Biology. , 23, 73, 2022

M.T. Dayao, M. Brusko, C. Wasserfall, and Z. Bar-Joseph Membrane marker selection for segmenting single cell spatial proteomics data. Nature Communications. , 13 (1), 1-10, 2022


J. Ding, N. Sharon, Z. Bar-Joseph Temporal modelling using single-cell transcriptomics.
Nat Rev Gene. , 23 (6), 355-368, 2022

Google Scholar

Highlighted Software

Dynamic Regulatory Events Miner (DREM)

Short Time-series Expression Miner (STEM)

All Software