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In this review, we examine an extended Bayesian inference method and its relation to biological information processing. We discuss the idea of combining two modes of Bayesian inference. The first is the standard Bayesian inference, which…

Other Statistics · Statistics 2023-07-04 Vasileios Basios , Yukio-Pegio Gunji , Pier-Francesco Moretti

The first realization of a designed, rather than natural, biochemical filter process is reported and analyzed as a promising network component for increasing the complexity of biomolecular logic systems. Key challenge in biochemical logic…

Biological Physics · Physics 2010-11-09 Vladimir Privman , Jan Halamek , Mary A. Arugula , Dmitriy Melnikov , Vera Bocharova , Evgeny Katz

Synthetic biologists have made great progress over the past decade in developing methods for modular assembly of genetic sequences and in engineering biological systems with a wide variety of functions in various contexts and organisms.…

Biomimicry is a powerful science that takes advantage of nature's remarkable ability to devise innovative solutions to challenging problems. In this work, we use asymptotic methods to develop the mathematical foundations for the exchange of…

Analysis of PDEs · Mathematics 2022-09-26 Habib Ammari , Bryn Davies

As a result of a hundred million years of evolution, living animals have adapted extremely well to their ecological niche. Such adaptation implies species-specific interactions with their immediate environment by processing sensory cues and…

Disordered Systems and Neural Networks · Physics 2022-04-28 Tom Birkoben , Hermann Kohlstedt

Signal transduction in biological cells is effected by signaling pathways that typically include multiple feedback loops. Here we analyze information transfer through a prototypical signaling module with biochemical feedback. The module…

Biological Physics · Physics 2015-11-06 Gerardo Aquino , Martin Zapotocky

As part of understanding how the brain learns, ongoing work seeks to combine biological knowledge and current artificial intelligence (AI) modeling in an attempt to find an efficient biologically plausible learning scheme. Current models of…

Artificial Intelligence · Computer Science 2024-06-18 Roy Abel , Shimon Ullman

In the past few decades, the life sciences have experienced an unprecedented accumulation of data, ranging from genomic sequences and proteomic profiles to heavy-content imaging, clinical assays, and commercial biological products for…

Databases · Computer Science 2025-09-22 Rosalia Moreddu

Causal ordering of key events in the cell cycle is essential for proper functioning of an organism. Yet, it remains a mystery how a specific temporal program of events is maintained despite ineluctable stochasticity in the biochemical…

Molecular Networks · Quantitative Biology 2017-03-30 Farshid Jafarpour , Michael Vennettilli , Srividya Iyer-Biswas

Biologically-inspired methods such as evolutionary algorithms and neural networks are proving useful in the field of information fusion. Artificial Immune Systems (AISs) are a biologically-inspired approach which take inspiration from the…

Artificial Intelligence · Computer Science 2010-07-05 Jamie Twycross , Uwe Aickelin

Escherichia coli has long been used as a model organism due to the extensive experimental characterization of its pathways and molecular components. Take chemotaxis as an example, which allows bacteria to sense and swim in response to…

Cell Behavior · Quantitative Biology 2015-12-09 Gabriele Micali , Robert G. Endres

Signal transduction, or signal-processing capability, is a fundamental property of nature that manifests universally across systems of different scales -- from quantum behaviour to the biological. This includes the detection of…

Signal Processing · Electrical Eng. & Systems 2023-09-12 Dorje C. Brody , Anthony J. Trewavas

With the recent advancements in artificial intelligence, researchers and industries are deploying gigantic models trained on billions of samples. While training these models consumes a huge amount of energy, human brains produce similar…

The discerning behavior of living systems relies on accurate interactions selected from the lot of molecular collisions occurring in the cell. To ensure the reliability of interactions, binding partners are classically envisioned as finely…

Molecular Networks · Quantitative Biology 2016-09-28 Denis Michel , Benjamin Boutin , Philippe Ruelle

Studies investigating neural information processing often implicitly ask both, which processing strategy out of several alternatives is used and how this strategy is implemented in neural dynamics. A prime example are studies on predictive…

Molecular circuits capable of autonomous learning could unlock novel applications in fields such as bioengineering and synthetic biology. To this end, existing chemical implementations of neural computing have mainly relied on emulating…

Machine Learning · Computer Science 2025-09-23 Rajiv Teja Nagipogu , John H. Reif

Information transmission in biological signaling circuits has often been described using the metaphor of a noise filter. Cellular systems need accurate, real-time data about their environmental conditions, but the biochemical reaction…

Molecular Networks · Quantitative Biology 2019-02-27 David Hathcock , James Sheehy , Casey Weisenberger , Efe Ilker , Michael Hinczewski

A central challenge in the origin of life is understanding how catalytic peptide-like polymers and information-bearing nucleic acid-like polymers emerged as an interde-pendent system. This study constructs a primordial cognitive model…

Other Quantitative Biology · Quantitative Biology 2026-05-11 Takeshi Ishida

Bio-inspired neural networks have the potential to advance our understanding of neural computation and improve the state-of-the-art of AI systems. Bio-electrical synapses directly transmit neural signals, by enabling fast current flow…

Neural and Evolutionary Computing · Computer Science 2024-01-18 Mónika Farsang , Mathias Lechner , David Lung , Ramin Hasani , Daniela Rus , Radu Grosu

Robustness to a wide variety of negative factors and the ability to self-repair is an inherent and natural characteristic of all life forms on earth. As opposed to nature, man-made systems are in most cases not inherently robust and a…

Neural and Evolutionary Computing · Computer Science 2016-11-15 Christof Teuscher