WorldCat Identities

Fior, Rita

Overview
Works: 3 works in 11 publications in 1 language and 214 library holdings
Roles: Editor, htt, Contributor, edi
Publication Timeline
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Most widely held works by Rita Fior
Molecular and cell biology of cancer : when cells break the rules and hijack their own planet( )

9 editions published in 2019 in English and held by 210 WorldCat member libraries worldwide

This textbook takes you on a journey to the basic concepts of cancer biology. It combines developmental, evolutionary and cell biology perspectives, to then wrap-up with an integrated clinical approach. The book starts with an introductory chapter, looking at cancer in a nut shell. The subsequent chapters are detailed and the idea of cancer as a mass of somatic cells undergoing a micro-evolutionary Darwinian process is explored. Further, the main Hanahan and Weinberg "Hallmarks of Cancer" are revisited. In most chapters, the fundamental experiments that led to key concepts, connecting basic biology and biomedicine are highlighted. In the book's closing section all of these concepts are integrated in clinical studies, where molecular diagnosis as well as the various classical and modern therapeutic strategies are addressed. The book is written in an easy-to-read language, like a one-on-one conversation between the writer and the reader, without compromising the scientific accuracy. Therefore, this book is suited not only for advanced undergraduates and master students but also for patients or curious lay people looking for a further understanding of this shattering disease
Object detection for automatic cancer cell counting in zebrafish xenografts( )

1 edition published in 2021 in English and held by 2 WorldCat member libraries worldwide

Cell counting is a frequent task in medical research studies. However, it is often performed manually; thus, it is time-consuming and prone to human error. Even so, cell counting auto- mation can be challenging to achieve, especially when dealing with crowded scenes and overlapping cells, assuming different shapes and sizes. In this paper, we introduce a deep learning-based cell detection and quantification methodology to automate the cell counting process in the zebrafish xenograft cancer model, an innovative technique for studying tumor biology and for personalizing medicine. First, we implemented a fine-tuned architecture based on the Faster R-CNN using the Inception ResNet V2 feature extractor. Second, we performed several adjustments to optimize the process, paying attention to constraints such as the presence of overlapped cells, the high number of objects to detect, the heterogeneity of the cells' size and shape, and the small size of the data set. This method resulted in a median error of approximately 1% of the total number of cell units. These results demon- strate the potential of our novel approach for quantifying cells in poorly labeled images. Compared to traditional Faster R-CNN, our method improved the average precision from 71% to 85% on the studied data set
A novel reporter of notch signalling indicates regulated and random notch activation during vertebrate neurogenesis by Filipe Vilas-Boas( )

1 edition published in 2011 in English and held by 2 WorldCat member libraries worldwide

 
Audience Level
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Audience Level
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  General Special  
Audience level: 0.54 (from 0.53 for Molecular ... to 0.97 for A novel re ...)

Molecular and cell biology of cancer : when cells break the rules and hijack their own planet
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Languages
English (11)