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Article detail · 2024

Structural analysis of genomic and proteomic signatures reveal dynamic expression of intrinsically disordered regions in breast cancer

Journal

iScience

ISSN 2589-0042

YÖKSİS OpenAlex Open access · gold SJR Q1 JCR Q1 Citations 2 Percentile 53.8% FWCI 0.3
Year
2024
Type
article

Data source split

  • YÖKSİS YÖKSİS article record
  • YÖKSİS venue iScience
  • Catalog match (ISSN) iScience
  • OpenAlex OpenAlex enrichment (abstract, citations, topics)

Abstract

OpenAlex · English

Structural features of proteins capture underlying information about protein evolution and function, which enhances the analysis of proteomic and transcriptomic data. Here, we develop Structural Analysis of Gene and protein Expression Signatures (SAGES), a method that describes expression data using features calculated from sequence-based prediction methods and 3D structural models. We used SAGES, along with machine learning, to characterize tissues from healthy individuals and those with breast cancer. We analyzed gene expression data from 23 breast cancer patients and genetic mutation data from the Catalog of Somatic Mutations In Cancer database as well as 17 breast tumor protein expression profiles. We identified prominent expression of intrinsically disordered regions in breast cancer proteins as well as relationships between drug perturbation signatures and breast cancer disease signatures. Our results suggest that SAGES is generally applicable to describe diverse biological phenomena including disease states and drug effects.

Topics

Citations

OpenAlex cited_by_count. Not a WoS or Scopus citation count; those sources have no separate column here.

2 citations

OpenAlex cited_by_count (cache / database)

Authors

  1. Nicole Zatorski
  2. Yifei Sun
  3. ABDÜLKADİR ELMAS NECMETTİN ERBAKAN ÜNİVERSİTESİ
  4. Christian Dallago
  5. Timothy Karl
  6. David Stein
  7. Burkhard Rost
  8. Kuan-lin Huang
  9. Martin Walsh
  10. Avner Schlessinger