Cell-cycle phase progression analysis identifies three unique phenotypes in soft tissue sarcoma

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Location: Deutsche Nationalbibliothek Frankfurt am Main

Extent: 1 Online-Ressource.

Language: Englisch

Bibliographic citation: Cell-cycle phase progression analysis identifies three unique phenotypes in soft tissue sarcoma ; volume:24 ; number:1 ; day:17 ; month:10 ; year:2024 ; pages:1-8 ; date:12.2024
BMC cancer ; 24, Heft 1 (17.10.2024), 1-8, 12.2024

Creator: Cullen, Mark M.
Lazarides, Alexander L.
Pittman, Patricia D.
Flamant, Etienne M.
Stoeber, Kathryn L.
Stoeber, Kai
Visguass, Julia D.
Brigman, Brian E.
Riedel, Richard F.
Cardona, Diana M.
Somarelli, Jason A.
Eward, William C.

Contributor: SpringerLink (Online service)

DOI: 10.1186/s12885-024-13043-6

URN: urn:nbn:de:101:1-2501062059303.145384510240

Rights: Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.

Last update: 15.08.2025, 7:38 AM CEST

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Cullen, Mark M.
Lazarides, Alexander L.
Pittman, Patricia D.
Flamant, Etienne M.
Stoeber, Kathryn L.
Stoeber, Kai
Visguass, Julia D.
Brigman, Brian E.
Riedel, Richard F.
Cardona, Diana M.
Somarelli, Jason A.
Eward, William C.
SpringerLink (Online service)

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Cell-cycle phase progression analysis identifies three unique phenotypes in soft tissue sarcoma

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Other Objects (12)

Transcriptional landscape of Kaposi sarcoma tumors identifies unique immunologic signatures and key determinants of angiogenesis

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High content analysis identifies unique morphological features of reprogrammed cardiomyocytes

Taxonomic reclassification of Kaposi Sarcoma identifies disease entities with distinct immunopathogenesis

Metabolomic profiling identifies distinct phenotypes for ASS1 positive and negative GBM

Correction to: Arginine derivatives in atrial fibrillation progression phenotypes

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Pseudoendocrine sarcoma: a rare new entity with unique radiologic and pathologic/molecular characteristics

Unsupervised machine learning identifies predictive progression markers of IPF

NELFE-Dependent MYC Signature Identifies a Unique Cancer Subtype in Hepatocellular Carcinoma

Transcriptional landscape of Kaposi sarcoma tumors identifies unique immunologic signatures and key determinants of angiogenesis

Proteomic characterization identifies clinically relevant subgroups of soft tissue sarcoma

Amyloid burden identifies neuropsychological phenotypes at increased risk of progression to Alzheimer’s disease in mild cognitive impairment patients

Magnetic-activated cell sorting identifies a unique lung microbiome community

High content analysis identifies unique morphological features of reprogrammed cardiomyocytes

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Metabolomic profiling identifies distinct phenotypes for ASS1 positive and negative GBM

Correction to: Arginine derivatives in atrial fibrillation progression phenotypes

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NELFE-Dependent MYC Signature Identifies a Unique Cancer Subtype in Hepatocellular Carcinoma

Transcriptional landscape of Kaposi sarcoma tumors identifies unique immunologic signatures and key determinants of angiogenesis

Proteomic characterization identifies clinically relevant subgroups of soft tissue sarcoma

Amyloid burden identifies neuropsychological phenotypes at increased risk of progression to Alzheimer’s disease in mild cognitive impairment patients

Magnetic-activated cell sorting identifies a unique lung microbiome community

High content analysis identifies unique morphological features of reprogrammed cardiomyocytes

Taxonomic reclassification of Kaposi Sarcoma identifies disease entities with distinct immunopathogenesis

Metabolomic profiling identifies distinct phenotypes for ASS1 positive and negative GBM

Correction to: Arginine derivatives in atrial fibrillation progression phenotypes

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Unsupervised machine learning identifies predictive progression markers of IPF

NELFE-Dependent MYC Signature Identifies a Unique Cancer Subtype in Hepatocellular Carcinoma

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