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1687 Publications visible to you, out of a total of 1687
Multi-view-AE: A Python package for multi-view autoencoder models

Abstract

Not specified

Authors: Ana Lawry Aguila, Alejandra Jayme, Nina Montaña-Brown, Vincent Heuveline, Andre Altmann

Date Published: 1st May 2023

Publication Type: Journal

Mathematical modeling of Lynch syndrome carcinogenesis

Abstract (Expand)

Cancer is one of the leading causes of disease-related death worldwide. In recent years, large amounts of data on cancer genetics and molecular characteristics have become available and accumulated … with increasing speed. However, the current understanding of cancer as a disease is still limited by the lack of suitable models that allow interpreting these data in proper ways. Thus, the highly interdisciplinary research field of mathematical oncology has evolved to use mathematics, modeling, and simulations to study cancer with the overall goal to improve clinical patient care. This dissertation aims at developing mathematical models and tools for different spatial scales of cancer development at the example of colorectal cancer in Lynch syndrome, the most common inherited colorectal cancer predisposition syndrome. We derive model-driven approaches for carcinogenesis at the DNA, cell, and crypt level, as well as data-driven methods for cancer-immune interactions at the DNA level and for the evaluation of diagnostic procedures at the Lynch syndrome population level. The developed models present an important step toward an improved understanding of hereditary cancer as a disease aiming at rapid implementation into clinical management guidelines and into the development of novel, innovative approaches for prevention and treatment.

Author: Saskia Haupt

Date Published: 28th Apr 2023

Publication Type: Doctoral Thesis

Model diagnostics meets forecast evaluation: Goodness-of-fit, calibration, and related topics

Abstract

Not specified

Author: Johannes Resin

Date Published: 20th Apr 2023

Publication Type: Doctoral Thesis

Toward a common standard for data and specimen provenance in life sciences

Abstract (Expand)

Open and practical exchange, dissemination, and reuse of specimens and data have become a fundamental requirement for life sciences research. The quality of the data obtained and thus the findings and … knowledge derived is thus significantly influenced by the quality of the samples, the experimental methods, and the data analysis. Therefore, a comprehensive and precise documentation of the pre-analytical conditions, the analytical procedures, and the data processing are essential to be able to assess the validity of the research results. With the increasing importance of the exchange, reuse, and sharing of data and samples, procedures are required that enable cross-organizational documentation, traceability, and non-repudiation. At present, this information on the provenance of samples and data is mostly either sparse, incomplete, or incoherent. Since there is no uniform framework, this information is usually only provided within the organization and not interoperably. At the same time, the collection and sharing of biological and environmental specimens increasingly require definition and documentation of benefit sharing and compliance to regulatory requirements rather than consideration of pure scientific needs. In this publication, we present an ongoing standardization effort to provide trustworthy machine-actionable documentation of the data lineage and specimens. We would like to invite experts from the biotechnology and biomedical fields to further contribute to the standard.

Authors: Rudolf Wittner, Petr Holub, Cecilia Mascia, Francesca Frexia, Heimo Müller, Markus Plass, Clare Allocca, Fay Betsou, Tony Burdett, Ibon Cancio, Adriane Chapman, Martin Chapman, Mélanie Courtot, Vasa Curcin, Johann Eder, Mark Elliot, Katrina Exter, Carole Goble, Martin Golebiewski, Bron Kisler, Andreas Kremer, Simone Leo, Sheng Lin‐Gibson, Anna Marsano, Marco Mattavelli, Josh Moore, Hiroki Nakae, Isabelle Perseil, Ayat Salman, James Sluka, Stian Soiland‐Reyes, Caterina Strambio‐De‐Castillia, Michael Sussman, Jason R. Swedlow, Kurt Zatloukal, Jörg Geiger

Date Published: 18th Apr 2023

Publication Type: Journal

A Gaussian process cross-correlation approach to time-delay estimation in active galactic nuclei

Abstract

Not specified

Authors: F. Pozo Nunez, N. Gianniotis, K.L. Polsterer

Date Published: 18th Apr 2023

Publication Type: Journal

Implementation Techniques for SPMD Kernels on CPUs

Abstract

Not specified

Authors: Joachim Meyer, Aksel Alpay, Sebastian Hack, Holger Fröning, Vincent Heuveline

Date Published: 18th Apr 2023

Publication Type: Journal

One Pass to Bind Them: The First Single-Pass SYCL Compiler with Unified Code Representation Across Backends

Abstract

Not specified

Authors: Aksel Alpay, Vincent Heuveline

Date Published: 18th Apr 2023

Publication Type: Journal

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