Proteomic profiling dataset of chemical perturbations in multiple biological backgrounds.
Sci Data
; 8(1): 226, 2021 08 25.
Article
en En
| MEDLINE
| ID: mdl-34433823
ABSTRACT
While gene expression profiling has traditionally been the method of choice for large-scale perturbational profiling studies, proteomics has emerged as an effective tool in this context for directly monitoring cellular responses to perturbations. We previously reported a pilot library containing 3400 profiles of multiple perturbations across diverse cellular backgrounds in the reduced-representation phosphoproteome (P100) and chromatin space (Global Chromatin Profiling, GCP). Here, we expand our original dataset to include profiles from a new set of cardiotoxic compounds and from astrocytes, an additional neural cell model, totaling 5300 proteomic signatures. We describe filtering criteria and quality control metrics used to assess and validate the technical quality and reproducibility of our data. To demonstrate the power of the library, we present two case studies where data is queried using the concept of "connectivity" to obtain biological insight. All data presented in this study have been deposited to the ProteomeXchange Consortium with identifiers PXD017458 (P100) and PXD017459 (GCP) and can be queried at https//clue.io/proteomics .
Texto completo:
1
Base de datos:
MEDLINE
Asunto principal:
Astrocitos
/
Proteómica
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Inhibidores de Proteínas Quinasas
/
Cardiotoxinas
/
Antineoplásicos
Tipo de estudio:
Prognostic_studies
Idioma:
En
Revista:
Sci Data
Año:
2021
Tipo del documento:
Article