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We propose generative neural network methods to generate DNA sequences and tune them to have desired properties. We present three approaches: creating synthetic DNA sequences using a generative adversarial network; a DNA-based variant of…

Machine Learning · Computer Science 2017-12-19 Nathan Killoran , Leo J. Lee , Andrew Delong , David Duvenaud , Brendan J. Frey

Over the last decade, kernel methods for nonlinear processing have successfully been used in the machine learning community. The primary mathematical tool employed in these methods is the notion of the Reproducing Kernel Hilbert Space.…

Machine Learning · Computer Science 2017-04-26 Pantelis Bouboulis , Sergios Theodoridis

Over the last decade, kernel methods for nonlinear processing have successfully been used in the machine learning community. However, so far, the emphasis has been on batch techniques. It is only recently, that online adaptive techniques…

Machine Learning · Computer Science 2010-05-26 Pantelis Bouboulis , Sergios Theodoridis

We present a mathematical study for the development of multiple sclerosis based on a reaction-diffusion system. The model describes interactions among different populations of human cells, motion of immune cells stimulated by cytokines,…

Tissues and Organs · Quantitative Biology 2026-01-07 Romina Travaglini

The Michaelis-Menten mechanism is probably the best known model for an enzyme-catalyzed reaction. For spatially homogeneous concentrations, QSS reductions are well known, but this is not the case when chemical species are allowed to…

Analysis of PDEs · Mathematics 2022-09-20 Martin Frank , Christian Lax , Sebastian Walcher , Olaf Wittich

In this paper, we present an automated approach for segmenting multiple sclerosis (MS) lesions from multi-modal brain magnetic resonance images. Our method is based on a deep end-to-end 2D convolutional neural network (CNN) for slice-based…

Computer Vision and Pattern Recognition · Computer Science 2019-04-09 Shahab Aslani , Michael Dayan , Loredana Storelli , Massimo Filippi , Vittorio Murino , Maria A Rocca , Diego Sona

Robust and generalizable segmentation of brain tumors on multi-parametric magnetic resonance imaging (MRI) remains difficult because tumor types differ widely. The BraTS 2025 Lighthouse Challenge benchmarks segmentation methods on diverse…

Multi Expression Programming (MEP) is a Genetic Programming variant which encodes multiple solutions in a single chromosome. This paper introduces and deeply describes several strategies for solving binary and multi-class classification…

Neural and Evolutionary Computing · Computer Science 2022-03-25 Mihai Oltean

Building better models of cellular pathways is one of the major challenges of systems biology and functional genomics. There is a need for methods to build on established expert knowledge and reconcile it with results of high-throughput…

Molecular Networks · Quantitative Biology 2014-06-25 Alexander Franks , Florian Markowetz , Edoardo Airoldi

We study a two-type branching process which provides excellent description of experimental data on cell dynamics in skin tissue (Clayton et al., 2007). The model involves only a single type of progenitor cell, and does not require support…

Populations and Evolution · Quantitative Biology 2010-11-18 Tibor Antal , P. L. Krapivsky

Single-cell RNA sequencing (scRNA-seq) is powerful technology that allows researchers to understand gene expression patterns at the single-cell level. However, analysing scRNA-seq data is challenging due to issues and biases in data…

Genomics · Quantitative Biology 2023-12-14 Jinlu Liu , Sara Wade , Natalia Bochkina

Recently, there has been a resurgence of interest in rigorous algorithms for the inference of cancer progression from genomic data. The motivations are manifold: (i) growing NGS and single cell data from cancer patients, (ii) need for novel…

Machine Learning · Computer Science 2016-02-25 Daniele Ramazzotti

Inferring concerted changes among biological traits along an evolutionary history remains an important yet challenging problem. Besides adjusting for spurious correlation induced from the shared history, the task also requires sufficient…

Quantum computing holds immense potential, yet its practical success depends on multiple factors, including advances in quantum circuit design. In this paper, we introduce a generative approach based on denoising diffusion models (DMs) to…

Quantum Physics · Physics 2025-07-24 Daniel Barta , Darya Martyniuk , Johannes Jung , Adrian Paschke

Motivated by a recent application of the Kolmogorov-Johnson-Mehl-Avrami (KJMA) model to the study of DNA replication, we consider the one-dimensional version of this model. We generalize previous work to the case where the nucleation rate…

Soft Condensed Matter · Physics 2009-11-10 Suckjoon Jun , Haiyang Zhang , John Bechhoefer

Potential theory is a central tool to understand and analyse Markov processes. In this article, we develop its probabilistic counterpart for branching Markov chains. Specifically, we examine versions of quasi-processes or interlacements…

Probability · Mathematics 2023-11-07 Steffen Dereich , Martin Maiwald

A large number and diversity of techniques have been offered in the literature in recent years for solving multi-label classification tasks, including classifier chains where predictions are cascaded to other models as additional features.…

Machine Learning · Computer Science 2019-07-19 Jesse Read , Luca Martino

In most natural sciences there is currently the insight that it is necessary to bridge gaps between different processes which can be observed on different scales. This is especially true in the field of chemical reactions where the…

Molecular Networks · Quantitative Biology 2008-03-03 L. Sbano , M. Kirkilionis

We present a model for growth in a multi-species population. We consider two types evolving as a logistic branching process with mutation, where one of the types has a selective advantage, and are interested in the regime in which the…

Probability · Mathematics 2025-07-18 Marta Dai Pra , Julian Kern

We consider designs for cancer trials which allow each medical centre to treat only a limited number of cancer types with only a limited number of drugs. We specify desirable properties of these designs, and prove some consequences. Then we…

Applications · Statistics 2019-05-31 R. A. Bailey , Peter J. Cameron