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This paper proposes a theory of encapsulation, establishing a relationship between encapsulation and information hiding through the concept of potential structural complexity (P.S.C.), the maximum possible number of source code dependencies…

Software Engineering · Computer Science 2008-07-29 Edmund Kirwan

The safe integration of machine learning modules in decision-making processes hinges on their ability to quantify uncertainty. A popular technique to achieve this goal is conformal prediction (CP), which transforms an arbitrary base…

Machine Learning · Computer Science 2024-01-23 Matteo Zecchin , Sangwoo Park , Osvaldo Simeone , Fredrik Hellström

At present, there is a great deal of confusion regarding complexity and its measures (reviews on complexity measures are found in, e.g. Lloyd, 2001 and Shalizi, 2006 and more references therein). Moreover, there is also confusion regarding…

Biological Physics · Physics 2012-05-01 Attila Grandpierre

This paper proposes an extension of the traditional Central Dogma of molecular biology to a more dynamic model termed the Central Dogma Cycle (CDC) and a broader network called the Central Dogma Cyclic Network (CDCN). While the Central…

Molecular Networks · Quantitative Biology 2025-06-23 Martin R. Schiller

In this paper, we make the case that a scientific theory of deep learning is emerging. By this we mean a theory which characterizes important properties and statistics of the training process, hidden representations, final weights, and…

A fascinating hypothesis is that human and animal intelligence could be explained by a few principles (rather than an encyclopedic list of heuristics). If that hypothesis was correct, we could more easily both understand our own…

Machine Learning · Computer Science 2022-08-02 Anirudh Goyal , Yoshua Bengio

Concept-based Models are a class of inherently explainable networks that improve upon standard Deep Neural Networks by providing a rationale behind their predictions using human-understandable `concepts'. With these models being highly…

Machine Learning · Computer Science 2025-06-06 Sanchit Sinha , Aidong Zhang

Memories are stored, retained, and recollected through complex, coupled processes operating on multiple timescales. To understand the computational principles behind these intricate networks of interactions we construct a broad class of…

Neurons and Cognition · Quantitative Biology 2015-07-29 Marcus K. Benna , Stefano Fusi

Until presently, most approaches for understanding physiological or pathological phenomena have been based on the assumption that these processes start from individual cells, a concept introduced primarily by Virchow in the 19th century.…

Subcellular Processes · Quantitative Biology 2007-11-02 Razvan Tudor Radulescu

Biological systems reach organizational complexity that far exceeds the complexity of any known inanimate objects. Biological entities undoubtedly obey the laws of quantum physics and statistical mechanics. However, is modern physics…

Other Quantitative Biology · Quantitative Biology 2018-02-26 Mikhail I. Katsnelson , Yuri I. Wolf , Eugene V. Koonin

Starting from the hypothesis that both physics, in particular space-time and the physical vacuum, and the corresponding mathematics are discrete on the Planck scale we develop a certain framework in form of a class of ' cellular networks'…

High Energy Physics - Theory · Physics 2016-09-06 Manfred Requardt

Entropy is arguably one of the most powerful concepts to understand the world, from the behavior of molecules to the expansion of the universe, from how life emerges to how hybrid complex systems like cities come into being and continue…

Physics and Society · Physics 2024-04-03 Vinicius M. Netto , Otavio Peres , Caio Cacholas

Despite substantial potential to transform bioscience, medicine, and bioengineering, whole-cell models remain elusive. One of the biggest challenges to whole-cell models is assembling the large and diverse array of data needed to model an…

Quantitative Methods · Quantitative Biology 2021-05-25 Yin Hoon Chew , Jonathan R. Karr

Cell formation problem is among the first obstacles the designer of cellular production systems must overcome. This paper presents a critical analysis of the various criteria and constraints considered in the literature. The objective is to…

Computational Engineering, Finance, and Science · Computer Science 2020-07-23 Menouar Boulif , Karim Atif

The theory of cellular automata in operational probabilistic theories is developed. We start introducing the composition of infinitely many elementary systems, and then use this notion to define update rules for such infinite composite…

Quantum Physics · Physics 2021-07-09 Paolo Perinotti

Modern biology and biomedicine are undergoing a big-data explosion needing advanced computational algorithms to extract mechanistic insights on the physiological state of living cells. We present the motivation for the Cell Physiome: a…

Cell Behavior · Quantitative Biology 2022-03-08 Vijay Rajagopal , Senthil Arumugam , Peter Hunter , Afshin Khadangi , Joshua Chung , Michael Pan

Human mobility is a fundamental process underpinning socioeconomic life and urban structure. Classic theories, such as egocentric activity spaces and central place theory, provide crucial insights into specific facets of movement, like…

Physics and Society · Physics 2025-05-22 Lu Zhong , Lei Dong , Qi Wang , Chaoming Song , Jianxi Gao

The path toward the emergence of life in our biosphere involved several key events allowing for the persistence, reproduction and evolution of molecular systems. All these processes took place in a given environmental context and required…

Disordered Systems and Neural Networks · Physics 2025-04-14 Ricard Solé , Manlio De Domenico

In this review, we discuss the applications of the theory of birth-and-death processes to problems in biology, primarily, those of evolutionary genomics. The mathematical principles of the theory of these processes are briefly described.…

Quantitative Methods · Quantitative Biology 2007-05-23 Artem S. Novozhilov , Georgy P. Karev , Eugene V. Koonin

Large scale models of physical phenomena demand the development of new statistical and computational tools in order to be effective. Many such models are `sloppy', i.e., exhibit behavior controlled by a relatively small number of parameter…