Results 141 to 150 of about 614,762 (328)

Cellular liquid biopsy provides unique chances for disease monitoring, preclinical model generation and therapy adjustment in rare salivary gland cancer patients

Molecular Oncology, EarlyView.
We quantified and cultured circulating tumor cells (CTCs) of 62 patients with various cancer types and generated CTC‐derived tumoroid models from two salivary gland cancer patients. Cellular liquid biopsy‐derived information enabled molecular genetic assessment of systemic disease heterogeneity and functional testing for therapy selection in both ...
Nataša Stojanović Gužvić, Florian Lüke, Steffi Treitschke, Andrea Coluccio, Martin Hoffmann, Giancarlo Feliciello, Adithi Ravikumar Varadarajan, Xin Lu, Kathrin Weidele, Catherine Botteron, Silvia Materna–Reichelt, Felix Keil, Katja Evert, Florian Weber, Thomas Schamberger, Michael Althammer, Jirka Grosse, Dirk Hellwig, Christian Schulz, Stephan Seitz, Peter Ugocsai, Anke Schlenska‐Lange, Roman Mayr, Ulrich Kaiser, Wolfgang Dietmaier, Bernhard Polzer, Jens Warfsmann, Kamran Honarnejad, Tobias Pukrop, Daniel Heudobler, Christoph A. Klein, Christian Werno   +31 more
wiley   +1 more source

Reproducing or constructing? Some questions about transcription in social research [PDF]

, 2010
Martyn Hammersley
openalex   +1 more source

Toward practical transparent verifiable and long-term reproducible research using Guix. [PDF]

Sci Data, 2022
Vallet N, Michonneau D, Tournier S.
europepmc   +1 more source

Combined spatially resolved metabolomics and spatial transcriptomics reveal the mechanism of RACK1‐mediated fatty acid synthesis

Molecular Oncology, EarlyView.
The authors analyzed the spatial distributions of gene and metabolite profiles in cervical cancer through spatial transcriptomic and spatially resolved metabolomic techniques. Pivotal genes and metabolites within these cases were then identified and validated.
Lixiu Xu, Jinqiu Li, Junqi Ma, Ayshamgul Hasim   +3 more
wiley   +1 more source

Reproducible research and the substantive context [PDF]

, 2010
Niels Keiding
openalex   +1 more source

CUF-Links: Continuous and Ubiquitous FAIRness Linkages for reproducible research. [PDF]

Computer (Long Beach Calif), 2022
Foster I, Kesselman C.
europepmc   +1 more source

Biomedical researchers’ perspectives on the reproducibility of research

PLOS Biology
We conducted an international cross-sectional survey of biomedical researchers’ perspectives on the reproducibility of research. This study builds on a widely cited 2016 survey on reproducibility and provides a biomedical-specific and contemporary perspective on reproducibility.
Kelly D. Cobey, Sanam Ebrahimzadeh, Matthew J. Page, Robert T. Thibault, Phi-Yen Nguyen, Farah Abu-Dalfa, David Moher   +6 more
openaire   +2 more sources

Circulating tumor DNA (ctDNA) trajectories predict survival in trifluridine/tipiracil‐treated metastatic colorectal cancer patients

Molecular Oncology, EarlyView.
The authors applied joint/mixed models that predict mortality of trifluridine/tipiracil‐treated metastatic colorectal cancer patients based on circulating tumor DNA (ctDNA) trajectories. Patients at high risk of death could be spared aggressive therapy with the prospect of a higher quality of life in their remaining lifetime, whereas patients with a ...
Matthias Unseld, Stefan Kühberger, Ricarda Graf, Christine Beichler, Markus Braun, Nadia Dandachi, Ellen Heitzer, Gerald W. Prager   +7 more
wiley   +1 more source

Ten simple rules for implementing open and reproducible research practices after attending a training course. [PDF]

PLoS Comput Biol, 2023
Heise V, Holman C, Lo H, Lyras EM, Adkins MC, Aquino MRJ, Bougioukas KI, Bray KO, Gajos M, Guo X, Hartling C, Huerta-Gutierrez R, Jindrová M, Kenney JPM, Kępińska AP, Kneller L, Lopez-Rodriguez E, Mühlensiepen F, Richards A, Richards G, Siebert M, Smith JA, Smith N, Stransky N, Tarvainen S, Valdes DS, Warrington KL, Wilpert NM, Witkowska D, Zaneva M, Zanker J, Weissgerber TL.   +31 more
europepmc   +1 more source

Reproducibility in Machine Learning-based Research: Overview, Barriers and Drivers [PDF]

arXiv
Many research fields are currently reckoning with issues of poor levels of reproducibility. Some label it a "crisis", and research employing or building Machine Learning (ML) models is no exception. Issues including lack of transparency, data or code, poor adherence to standards, and the sensitivity of ML training conditions mean that many papers are ...
arxiv