UCLA Department of Chemistry & Biochemistry



Open access research resources created by the Torres lab with generous funding
from the National Science Foundation, NSF MCB1243645.


CANVS is a computational pipeline that cleans, analyzes, and visualizes mass
spectrometry-based interactome/association data. CANVS is wrapped as an
interactive Shiny dashboard, allowing users to easily interface with
the pipeline. With simple requirements, users can analyze complex experimental
data and create PPI/A networks. The application integrates systems biology
databases like BioGRID and CORUM to contextualize the results. Furthermore,
CANVS features a Gene Ontology tool that allows users to identify relevant
GO terms in their results and create visual networks with proteins associated
with relevant GO terms. Overall, CANVS is an easy-to-use application that benefits
all researchers, especially those who lack an established bioinformatic pipeline
and are interested in studying interactome/association data.

Published Artticle:
Velasquez E.F., Garcia Y.A., Ramirez I., Gholkar A.A., and Torres J.Z. “CANVS: an easy-to-use application for the analysis and visualization of mass spectrometry-based protein-protein interaction/association data, Molecular Biology of the Cell 2021 Aug 25: mbcE21050257, doi: 10.1091/mbc.E21-05-0257. PMID: 34432510

CSNAP web server: CSNAP

CSNAP (Chemical Similarity Network Analysis Pull-down) is a computational approach
for compound target identification based on network chemical similarity graphs.
Query and reference compounds are populated on the network connectivity map and
a graph-based neighbor counting method is applied to rank the consensus targets
among the neighborhood of each query ligand. The CSNAP approach can facilitate
high-throughput target discovery and off-target prediction for any compound set
identified from phenotype-based or cell-based chemical screens.

Published Artticle:
Lo, Y.C., Senese, S., Li, C.M., Hu, Q., Huang, Y., Damoiseaux, R., Torres, J.Z. "Large-scale Chemical Similarity Networks for Drug Target Profiling of Compounds Identified in Cell-based Chemical Screens." PLoS Comput Biol. 11(3) (2015) [PMID:25826798]

Generation of Inducible LAP-tagged stable cell lines and LAP biochemical purifications video:


Video describe a method for generating localization and affinity purification (LAP)-tagged inducible stable cell lines for investigating protein function, spatiotemporal subcellular localization and protein-protein interaction networks.

Published article:
Bradley M., Ramirez I., Cheung K., Gholkar A.A., and Torres J.Z. “Inducible LAP-tagged Stable Cell Lines for Investigating Protein Function, Spatiotemporal Localization and Protein Interaction Networks”, Journal of Visualized Experiments 2016 Dec. 24, (118):1-9, e54870, doi:10.3791/54870. PMID:28060263


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