Results 21 to 30 of about 801,900 (223)

Investigation of the Uniformity of Gel Shrinkage by Imaging Tracer Particles Using X‐Ray Microtomography

Advanced Engineering Materials, EarlyView., 2023
A novel method for tracking structural changes in gels using widely accessible microcomputed tomography is presented and validated for various hydro‐, alco‐, and aerogels. The core idea of the method is to track positions of micrometer‐sized tracer particles entrapped in the gel and relate them to the density of the gel network.
Anja Hajnal, Mimololorun Lucy Aiyelari, Martin Dirauf, Pavel Gurikov   +3 more
wiley   +1 more source

Addressing persistent challenges in digital image analysis of cancer tissue: resources developed from a hackathon

Molecular Oncology, EarlyView.
Large multidimensional digital images of cancer tissue are becoming prolific, but many challenges exist to automatically extract relevant information from them using computational tools. We describe publicly available resources that have been developed jointly by expert and non‐expert computational biologists working together during a virtual hackathon
Sandhya Prabhakaran, Clarence Yapp, Gregory J. Baker, Johanna Beyer, Young Hwan Chang, Allison L. Creason, Robert Krueger, Jeremy Muhlich, Nathan Heath Patterson, Kevin Sidak, Damir Sudar, Adam J. Taylor, Luke Ternes, Jakob Troidl, Xie Yubin, Artem Sokolov, Darren R. Tyson   +16 more
wiley   +1 more source

Integration of single‐cell and bulk RNA‐sequencing data reveals the prognostic potential of epithelial gene markers for prostate cancer

Molecular Oncology, EarlyView.
Prostate cancer is a leading malignancy with significant clinical heterogeneity in men. An 11‐gene signature derived from dysregulated epithelial cell markers effectively predicted biochemical recurrence‐free survival in patients who underwent radical surgery or radiotherapy.
Zhuofan Mou, Lorna W. Harries
wiley   +1 more source

Exploration of heterogeneity and recurrence signatures in hepatocellular carcinoma

Molecular Oncology, EarlyView.
This study leveraged public datasets and integrative bioinformatic analysis to dissect malignant cell heterogeneity between relapsed and primary HCC, focusing on intercellular communication, differentiation status, metabolic activity, and transcriptomic profiles.
Wen‐Jing Wu, Jianchao Wang, Fuqing Chen, Xuefeng Wang, Bin Lan, Ruyi Fu, Hong Wen, Fangfang Chen, Wei Hong, Tian‐Yu Tang, Ying He, Gang Chen, Jianyin Zhou, Hai‐Long Piao, Di Chen, Shu‐Yong Lin   +15 more
wiley   +1 more source

Comparing self‐reported race and genetic ancestry for identifying potential differentially methylated sites in endometrial cancer: insights from African ancestry proportions using machine learning models

Molecular Oncology, EarlyView.
Integrating ancestry, differential methylation analysis, and machine learning, we identified robust epigenetic signature genes (ESGs) and Core‐ESGs in Black and White women with endometrial cancer. Core‐ESGs (namely APOBEC1 and PLEKHG5) methylation levels were significantly associated with survival, with tumors from high African ancestry (THA) showing ...
Huma Asif, J. Julie Kim
wiley   +1 more source

A large‐scale retrospective study in metastatic breast cancer patients using circulating tumour DNA and machine learning to predict treatment outcome and progression‐free survival

Molecular Oncology, EarlyView.
There is an unmet need in metastatic breast cancer patients to monitor therapy response in real time. In this study, we show how a noninvasive and affordable strategy based on sequencing of plasma samples with longitudinal tracking of tumour fraction paired with a statistical model provides valuable information on treatment response in advance of the ...
Emma J. Beddowes, Mario Ortega Duran, Solon Karapanagiotis, Alistair Martin, Meiling Gao, Riccardo Masina, Ramona Woitek, James Tanner, Fleur Tippin, Justine Kane, Jonathan Lay, Anja Brouwer, Stephen‐John Sammut, Suet‐Feung Chin, Davina Gale, Dana W. Y. Tsui, Sarah‐Jane Dawson, Nitzan Rosenfeld, Maurizio Callari, Oscar M. Rueda, Carlos Caldas   +20 more
wiley   +1 more source

Time, the final frontier

Molecular Oncology, EarlyView.
This article advocates integrating temporal dynamics into cancer research. Rather than relying on static snapshots, researchers should increasingly consider adopting dynamic methods—such as live imaging, temporal omics, and liquid biopsies—to track how tumors evolve over time.
Gautier Follain, Michal Dibus, Omkar Joshi, Guillaume Jacquemet   +3 more
wiley   +1 more source

Blended Learning Content Generation: A Guide for Busy Academics [PDF]

arXiv, 2020
A practical guide for university academics who need to create learning materials that support flexible delivery methods. Examples from the Computer Science domain are used to illustrate innovative approaches to engaging students with online and blended teaching resources.
arxiv  

A Statistical and Machine Learning Approach for Summarising Computer Science Research Papers [PDF]

, 2023
Sheik Muhammad Wakeel Bauboorally, Sameerchand Pudaruth   +1 more
openalex   +1 more source

Participating in a Computer Science Linked-courses Learning Community Reduces Isolation [PDF]

arXiv, 2017
In our previous work we reported on a linked-courses learning community for underrepresented groups in computer science, finding differences in attitudes and resource utilization between students in the community and other programming students. Here we present the first statistically significant differences in pre- to post-quarter student attitudes ...
arxiv