Results 91 to 100 of about 99,185 (278)

Data‐driven discovery of gene expression markers distinguishing pediatric acute lymphoblastic leukemia subtypes

open access: yesMolecular Oncology, EarlyView.
This study investigates gene expression differences between two major pediatric acute lymphoblastic leukemia (ALL) subtypes, B‐cell precursor ALL, and T‐cell ALL, using a data‐driven approach consisting of biostatistics and machine learning methods. Following analysis of a discovery dataset, we find a set of 14 expression markers differentiating the ...
Mona Nourbakhsh   +8 more
wiley   +1 more source

Méthodes de surclassement et analyse de robustesse [PDF]

open access: yesBiotechnologie, Agronomie, Société et Environnement, 2001
Outranking methods and robustness analysis. The introduction gives the arguments on which the choice of outranking methods is based: application domain, existence of a software, lack of works on the robustness of outranking methods.
Ben-Mena S.
doaj  

Comprehensive omics‐based classification system in adult patients with B‐cell acute lymphoblastic leukemia

open access: yesMolecular Oncology, EarlyView.
The COMBAT classification system, developed through multi‐omics integration, stratifies adult patients with B‐cell acute lymphoblastic leukemia(B‐ALL) into three molecular subtypes with distinct surface antigen patterns, immune landscape, methylation patterns, biological pathways and prognosis.
Yang Song   +11 more
wiley   +1 more source

Tumor clusters with divergent inflammation and human retroelement expression determine the clinical outcome of patients with serous ovarian cancer

open access: yesMolecular Oncology, EarlyView.
Analysis of treatment‐naïve high‐grade serous ovarian carcinoma (HGSOC) and control tissues for ERVs, LINE‐1 (L1), inflammation, and immune checkpoints identified five clusters with diverse patient recurrence‐free survivals. An inflammation score was calculated and correlated with retroelement expression, where one novel cluster (Triple‐I) with high ...
Laura Glossner   +6 more
wiley   +1 more source

EGFR‐STAT3 activation provides a therapeutic rationale for targeting aggressive ETV1‐positive prostate cancer

open access: yesMolecular Oncology, EarlyView.
Cotargeting EGFR and STAT3 with Erlotinib and TTI‐101 impairs both 2D and 3D growth of ETV1‐overexpressing prostate cancer cells by disrupting a self‐sustaining ETV1–EGFR positive feedback loop that promotes EGFR and STAT3 expression and phosphorylation (activation).
Elsa Gomes Paiva   +5 more
wiley   +1 more source

Biological Robustness: Paradigms, Mechanisms, and Systems Principles

open access: yesFrontiers in Genetics, 2012
Robustness has been studied through the analysis of data sets, simulations, and a variety of experimental techniques that each have their own limitations but together confirm the ubiquity of biological robustness.
James Michael Whitacre
doaj   +1 more source

Robustness of Phylogenetic Inference Based on Minimum Evolution

open access: yesBulletin of Mathematical Biology, 2010
Minimum evolution is the guiding principle of an important class of distance-based phylogeny reconstruction methods, including neighbor-joining (NJ), which is the most cited tree inference algorithm to date. The minimum evolution principle involves searching for the tree with minimum length, where the length is estimated using various least-squares ...
Olivier Gascuel   +3 more
openaire   +4 more sources

Integrative miRNOMe profiling reveals the miR‐195‐5p–CHEK1 axis and its impact on luminal breast cancer outcomes

open access: yesMolecular Oncology, EarlyView.
In luminal (ER+) breast carcinoma (BC), miRNA profiling identified miR‐195‐5p as a key regulator of proliferation that targets CHEK1, CDC25A, and CCNE1. High CHEK1 expression correlates with worse relapse‐free survival after chemotherapy, especially in patients with luminal A subtype.
Veronika Boušková   +14 more
wiley   +1 more source

Machine learning for identifying liver and pancreas cancers through comprehensive serum glycopeptide spectra analysis: a case‐control study

open access: yesMolecular Oncology, EarlyView.
This study presents a novel AI‐based diagnostic approach—comprehensive serum glycopeptide spectra analysis (CSGSA)—that integrates tumor markers and enriched glycopeptides from serum. Using a neural network model, this method accurately distinguishes liver and pancreatic cancers from healthy individuals.
Motoyuki Kohjima   +6 more
wiley   +1 more source

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