Results 151 to 160 of about 2,663,721 (268)

Characterizing the salivary RNA landscape to identify potential diagnostic, prognostic, and follow‐up biomarkers for breast cancer

Molecular Oncology, EarlyView.
This study explores salivary RNA for breast cancer (BC) diagnosis, prognosis, and follow‐up. High‐throughput RNA sequencing identified distinct salivary RNA signatures, including novel transcripts, that differentiate BC from healthy controls, characterize histological and molecular subtypes, and indicate lymph node involvement.
Nicholas Rajan, Irina Primac, Emre Etlioglu, Laurens Debruyne, Ann Janssen, Magy Sallam, Kevin Tabury, Roel Quintens, Wiebren Tjalma, Mohammed Abderrafi Benotmane   +9 more
wiley   +1 more source

Importance Sampling

, 2020
Nicolas Chopin, Omiros Papaspiliopoulos
openaire   +1 more source

Bridging the gap: Multi‐stakeholder perspectives of molecular diagnostics in oncology

Molecular Oncology, EarlyView.
Although molecular diagnostics is transforming cancer care, implementing novel technologies remains challenging. This study identifies unmet needs and technology requirements through a two‐step stakeholder involvement. Liquid biopsies for monitoring applications and predictive biomarker testing emerge as key unmet needs. Technology requirements vary by
Jorine Arnouts, Senada Koljenović, Elise Daems, Karolien De Wael, Marc Peeters, Léon C. van Kempen, Greetje Vanhoutte, Karen Zwaenepoel, Timon Vandamme   +8 more
wiley   +1 more source

Bayesian Update with Importance Sampling: Required Sample Size. [PDF]

Entropy (Basel), 2020
Sanz-Alonso D, Wang Z.
europepmc   +1 more source

Adenosine‐to‐inosine editing of miR‐200b‐3p is associated with the progression of high‐grade serous ovarian cancer

Molecular Oncology, EarlyView.
A‐to‐I editing of miRNAs, particularly miR‐200b‐3p, contributes to HGSOC progression by enhancing cancer cell proliferation, migration and 3D growth. The edited form is linked to poorer patient survival and the identification of novel molecular targets.
Magdalena Niemira, Anna Skwarska, Karolina Chwialkowska, Agnieszka Ostrowska, Gabriela Sokolowska, Anna Zeller, Anna Erol, Andrzej Eljaszewicz, Bartosz Hanczaruk, Anna Michalska‐Falkowska, Agnieszka Tarasik, Joanna Reszec‐Gielazyn, Pawel Knapp, Marcin Moniuszko, Adam Kretowski   +14 more
wiley   +1 more source

A Robust Solution to Variational Importance Sampling of Minimum Variance. [PDF]

Entropy (Basel), 2020
Hernández-González J, Cerquides J.
europepmc   +1 more source

Off-Policy Evaluation of the Performance of a Robot Swarm: Importance Sampling to Assess Potential Modifications to the Finite-State Machine That Controls the Robots. [PDF]

Front Robot AI, 2021
Pagnozzi F, Birattari M.
europepmc   +1 more source

Investigating the cell of origin and novel molecular targets in Merkel cell carcinoma: a historic misnomer

Molecular Oncology, EarlyView.
This study indicates that Merkel cell carcinoma (MCC) does not originate from Merkel cells, and identifies gene, protein & cellular expression of immune‐linked and neuroendocrine markers in primary and metastatic Merkel cell carcinoma (MCC) tumor samples, linked to Merkel cell polyomavirus (MCPyV) status, with enrichment of B‐cell and other immune cell
Richie Jeremian, Sriraam Sivachandran, Melissa Galati, Brandon Ramchatesingh, Hibo Rijal, Johnny Hanna, Elena Netchiporouk, May Chergui, Margaret Redpath, Samy Abou Setah, Ivan V. Litvinov   +10 more
wiley   +1 more source

YAP1::TFE3 mediates endothelial‐to‐mesenchymal plasticity in epithelioid hemangioendothelioma

Molecular Oncology, EarlyView.
The YAP1::TFE3 fusion protein drives endothelial‐to‐mesenchymal transition (EndMT) plasticity, resulting in the loss of endothelial characteristics and gain of mesenchymal‐like properties, including resistance to anoikis, increased migratory capacity, and loss of contact growth inhibition in endothelial cells.
Ant Murphy, Samuel Hartzler, Paula A. Vargas Carranza, Shyaman Jayasundara, Madison E. Yates, Nimod D. Janson, Bozhi Liu, Annaleigh Benton, Majid Kazemian, Jason A. Hanna   +9 more
wiley   +1 more source

Looking elsewhere: improving variational Monte Carlo gradients by importance sampling

Machine Learning: Science and Technology
Neural-network quantum states (NQSs) offer a powerful and expressive ansatz for representing quantum many-body wave functions. However, their training via Variational Monte Carlo (VMC) methods remains challenging.
Antoine Misery, Luca Gravina, Alessandro Santini, Filippo Vicentini   +3 more
doaj   +1 more source