Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Video

Updated: Sep 22, 2025

Purification of the Cystic Fibrosis Transmembrane Conductance Regulator Protein Expressed in Saccharomyces cerevisiae
15:12

Purification of the Cystic Fibrosis Transmembrane Conductance Regulator Protein Expressed in Saccharomyces cerevisiae

Published on: May 10, 2014

14.6K

Pollock: fishing for cell states.

Erik P Storrs1,2, Daniel Cui Zhou1,2, Michael C Wendl1,2

  • 1Department of Medicine, Washington University in St. Louis, St. Louis, MO 63110, USA.

Bioinformatics Advances
|May 23, 2022
PubMed
Summary

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Integrated proteogenomic and metabolomic profiling of acute myeloid leukemias to identify molecular subtypes and associated therapy targets.

Nature cancer·2026
Same author

Spatial Mapping of the Precancer-to-Cancer Transition in Breast and Prostate.

Cancer discovery·2026
Same author

LDHA-driven lactate metabolism promotes MDSC activation and immunosuppressive microenvironment in prostate cancer.

Oncogene·2026
Same author

Chemoradiation Reprograms Tumor Cells and the Immune Microenvironment in Cervical Cancer.

Cancer research·2026
Same author

OmniCellTOSG: The First Cell Text-Omic Signaling Graphs Dataset for Graph Language Foundation Modeling.

Research square·2026
Same author

Biomarkers of response to neoadjuvant palbociclib plus anastrozole in endocrine-resistant estrogen receptor-positive/HER2-negative breast cancer: a phase 2 trial.

Nature communications·2026
This summary is machine-generated.

We developed Pollock, a new cell type identification tool for single-cell analysis. It offers cross-platform compatibility and interpretable results, outperforming existing methods in cancer research.

Area of Science:

  • Computational biology
  • Genomics
  • Bioinformatics

Background:

  • Single-cell analysis is rapidly advancing, necessitating robust cell classification methods.
  • Existing cell classification algorithms face limitations in cross-platform compatibility, reference dataset dependency, and interpretability.

Purpose of the Study:

  • Introduce Pollock, a novel suite of algorithms for cell type identification.
  • Address limitations of current single-cell classification tools.

Main Methods:

  • Developed Pollock, a suite of algorithms for cell type identification.
  • Integrated cross-platform compatibility with popular single-cell analysis methods.
  • Created pretrained human cancer reference models.

Main Results:

More Related Videos

A New Best Practice for Validating Tail Vein Injections in Rat with Near-infrared-Labeled Agents
04:19

A New Best Practice for Validating Tail Vein Injections in Rat with Near-infrared-Labeled Agents

Published on: April 19, 2019

21.4K

Related Experiment Videos

Last Updated: Sep 22, 2025

Purification of the Cystic Fibrosis Transmembrane Conductance Regulator Protein Expressed in Saccharomyces cerevisiae
15:12

Purification of the Cystic Fibrosis Transmembrane Conductance Regulator Protein Expressed in Saccharomyces cerevisiae

Published on: May 10, 2014

14.6K
A New Best Practice for Validating Tail Vein Injections in Rat with Near-infrared-Labeled Agents
04:19

A New Best Practice for Validating Tail Vein Injections in Rat with Near-infrared-Labeled Agents

Published on: April 19, 2019

21.4K
  • Pollock demonstrates comparable performance to existing classification methods.
  • Offers easily deployable pretrained models across diverse tissue and data types.
  • Shows utility in immune pan-cancer analysis.

Conclusions:

  • Pollock provides a versatile and interpretable solution for single-cell type identification.
  • Facilitates broader adoption of advanced cell classification in research.
  • Enables robust pan-cancer immune profiling.