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Background. Emerging technologies now allow for mass spectrometry based profiling of up to thousands of small molecule metabolites (metabolomics) in an increasing number of biosamples. While offering great promise for revealing insight into…

A mathematical model for time development of metastases and their distribution in size and carrying capacity is presented. The model is used to theoretically investigate anti-cancer therapies such as surgery and chemical treatments…

Tissues and Organs · Quantitative Biology 2013-06-21 Sebastien Benzekry , Dominique Barbolosi , Assia Benabdallah , Florence Hubert , Philip Hahnfeldt

An extensive rewiring of cell metabolism supports enhanced proliferation in cancer cells. We propose a systems level approach to describe this phenomenon based on Flux Balance Analysis (FBA). The approach does not explicit a cell biomass…

Computational Engineering, Finance, and Science · Computer Science 2013-10-01 Chiara Damiani , Riccardo Colombo , Sara Molinari , Dario Pescini , Daniela Gaglio , Marco Vanoni , Lilia Alberghina , Giancarlo Mauri

In cancer research, clustering techniques are widely used for exploratory analyses and dimensionality reduction, playing a critical role in the identification of novel cancer subtypes, often with direct implications for patient management.…

In this study, we develop consistent estimators for key parameters that govern the dynamics of tumor cell populations when subjected to pharmacological treatments. While these treatments often lead to an initial reduction in the abundance…

Applications · Statistics 2024-03-21 Kevin Leder , Ruping Sun , Zicheng Wang , Xuanming Zhang

With the long-term rapid increase in incidences of colorectal cancer (CRC), there is an urgent clinical need to improve risk stratification. The conventional pathology report is usually limited to only a few histopathological features.…

Image and Video Processing · Electrical Eng. & Systems 2020-07-08 Christian Abbet , Inti Zlobec , Behzad Bozorgtabar , Jean-Philippe Thiran

Due to the complexity of cancer, clustering algorithms have been used to disentangle the observed heterogeneity and identify cancer subtypes that can be treated specifically. While kernel based clustering approaches allow the use of more…

Machine Learning · Statistics 2018-11-21 Nora K. Speicher , Nico Pfeifer

Nuanced cancer patient care is needed, as the development and clinical course of cancer is multifactorial with influences from the general health status of the patient, germline and neoplastic mutations, co-morbidities, and environment. To…

Quantitative Methods · Quantitative Biology 2023-09-26 Ali Firooz , Avery T. Funkhouser , Julie C. Martin , W. Jeffery Edenfield , Homayoun Valafar , Anna V. Blenda

Personalized diagnoses have not been possible due to sear amount of data pathologists have to bear during the day-to-day routine. This lead to the current generalized standards that are being continuously updated as new findings are…

Computer Vision and Pattern Recognition · Computer Science 2021-10-27 Jialun Wu , Zeyu Gao , Haichuan Zhang , Ruonan Zhang , Tieliang Gong , Chunbao Wang , Chen Li

The task of clustering a set of objects based on multiple sources of data arises in several modern applications. We propose an integrative statistical model that permits a separate clustering of the objects for each data source. These…

Machine Learning · Statistics 2015-12-01 Eric F. Lock , David B. Dunson

Recent works have stressed the important role that random mutations have in the development of cancer phenotype. We challenge this current view by means of bioinformatic data analysis and computational modelling approaches. Not all the…

Cell Behavior · Quantitative Biology 2017-06-28 Gianluca Ascolani , Pietro Lió

Cancer cell lines have frequently been used to link drug sensitivity and resistance with genomic profiles. To capture genomic complexity in cancer, the Cancer Genome Project (CGP) (Garnett et al., 2012) screened 639 human tumor cell lines…

Applications · Statistics 2017-02-09 Hongmei Liu , J. Sunil Rao

In cancer research, high-throughput profiling has been extensively conducted. In recent studies, the integrative analysis of data on multiple cancer patient groups/subgroups has been conducted. Such analysis has the potential to reveal the…

Methodology · Statistics 2022-12-01 Yifan Sun , Zhengyang Sun , Yu Jiang , Yang Li , Shuangge Ma

Metabolomic data sets provide a direct read-out of cellular phenotypes and are increasingly generated to study biological questions. Our previous work revealed the potential of analyzing extracellular metabolomic data in the context of the…

Molecular Networks · Quantitative Biology 2016-06-10 Maike K. Aurich , Ronan M. T. Fleming , Ines Thiele

We utilized abundant transcriptomic data for the primary classes of brain cancers to study the feasibility of separating all of these diseases simultaneously based on molecular data alone. These signatures were based on a new method…

Quantitative Methods · Quantitative Biology 2013-08-05 Jaeyun Sung , Pan-Jun Kim , Shuyi Ma , Cory C. Funk , Andrew T. Magis , Yuliang Wang , Leroy Hood , Donald Geman , Nathan D. Price

In this paper, we describe a dataset relating to cellular and physical conditions of patients who are operated upon to remove colorectal tumours. This data provides a unique insight into immunological status at the point of tumour removal,…

Machine Learning · Computer Science 2016-11-15 Chris Roadknight , Uwe Aickelin , John Scholefield , Lindy Durrant

Late diagnosis and high costs are key factors that negatively impact the care of cancer patients worldwide. Although the availability of biological markers for the diagnosis of cancer type is increasing, costs and reliability of tests…

Machine Learning · Computer Science 2019-08-20 Sterling Ramroach , Melford John , Ajay Joshi

International initiatives such as METABRIC (Molecular Taxonomy of Breast Cancer International Consortium) have collected several multigenomic and clinical data sets to identify the undergoing molecular processes taking place throughout the…

Machine Learning · Computer Science 2022-11-29 Teodora Reu

We propose a new approach for clustering DNA features using array CGH data from multiple tumor samples. We distinguish data-collapsing: joining contiguous DNA clones or probes with extremely similar data into regions, from clustering:…

Applications · Statistics 2010-12-21 Kyung In Kim , Etienne Roquain , Mark Van De Wiel

In vivo H nuclear magnetic resonance (NMR) spectroscopy is an important tool for performing non-invasive quantitative assessments of brain tumour glucose metabolism. Brain tumours are considered fast-growth tumours because of their high…

Biological Physics · Physics 2010-10-15 Alejandro Chinea Manrique de Lara