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Biomedical research centers can empower basic discovery and novel therapeutic strategies by leveraging their large-scale datasets from experiments and patients. This data, together with new technologies to create and analyze it, has ushered…

The aim of this work is to make available to the community a large collection of mass-action reaction networks of a given size for further research. The set is limited to what can be computed on a modern multi-core desktop in reasonable…

Molecular Networks · Quantitative Biology 2009-01-21 Anastasia C. Deckard , Frank T. Bergmann , Herbert M. Sauro

Traditional Evolutionary Robotics (ER) employs evolutionary techniques to search for a single monolithic controller which can aid a robot to learn a desired task. These techniques suffer from bootstrap and deception issues when the tasks…

Neural and Evolutionary Computing · Computer Science 2018-06-27 Tushar Semwal , Divya D Kulkarni , Shivashankar B. Nair

Artificial intelligence (AI) techniques are widely applied in the life sciences. However, applying innovative AI techniques to understand and deconvolute biological complexity is hindered by the learning curve for life science scientists to…

Artificial Intelligence · Computer Science 2024-03-28 Nisha Pillai , Athish Ram Das , Moses Ayoola , Ganga Gireesan , Bindu Nanduri , Mahalingam Ramkumar

We consider the problem of developing suitable learning representations (embeddings) for library packages that capture semantic similarity among libraries. Such representations are known to improve the performance of downstream learning…

Software Engineering · Computer Science 2019-04-09 Bart Theeten , Frederik Vandeputte , Tom Van Cutsem

The quest to understand structure-function relationships in networks across scientific disciplines has intensified. However, the optimal network architecture remains elusive, particularly for complex information processing. Therefore, we…

Adaptation and Self-Organizing Systems · Physics 2024-03-27 Manish Yadav , Sudeshna Sinha , Merten Stender

This paper is placed at the intersection-point between the study of theoretical computational models aimed at capturing the essence of genetic regulatory networks and the field of Artificial Embryology (or Computational Development). A…

Adaptation and Self-Organizing Systems · Physics 2016-10-12 Alessandro Fontana

Bio-inspired algorithms utilize natural processes such as evolution, swarm behavior, foraging, and plant growth to solve complex, nonlinear, high-dimensional optimization problems. However, a plethora of these algorithms require a more…

Hybrid-Lambda is a software package that simulates gene trees under Kingman or two Lambda-coalescent processes within species networks or species trees. It is written in C++, and re- leased under GNU General Public License (GPL) version 3.…

Populations and Evolution · Quantitative Biology 2013-03-05 Sha Zhu , James H Degnan , Bjarki Eldon

We describe a software package called VPLanet that simulates fundamental aspects of planetary system evolution over Gyr timescales, with a focus on investigating habitable worlds. In this initial release, eleven physics modules are included…

Randomized libraries are increasingly popular in protein engineering and other biomedical research fields. Statistics of the libraries are useful to guide and evaluate randomized library construction. Previous works only give the mean of…

Quantitative Methods · Quantitative Biology 2024-05-28 Yong Kong

In this work, a conceptual bio-inspired parallel and distributed learning framework for the emergence of general intelligence is proposed, where agents evolve through environmental rewards and learn throughout their lifetime without…

Neural and Evolutionary Computing · Computer Science 2020-09-23 Sidney Pontes-Filho , Stefano Nichele

We report a summary of our interdisciplinary research project "Evolutionary Perspective on Collective Decision Making" that was conducted through close collaboration between computational, organizational and social scientists at Binghamton…

Neural and Evolutionary Computing · Computer Science 2017-05-29 Hiroki Sayama , Shelley D. Dionne

A central biological question is how natural organisms are so evolvable (capable of quickly adapting to new environments). A key driver of evolvability is the widespread modularity of biological networks--their organization as functional,…

Populations and Evolution · Quantitative Biology 2015-03-13 Jeff Clune , Jean-Baptiste Mouret , Hod Lipson

The emergence of multicellularity and developmental programs are among the major problems of evolutionary biology. Traditionally, research in this area has been based on the combination of data analysis and experimental work on one hand and…

Populations and Evolution · Quantitative Biology 2014-03-14 Ricard V. Solé , Salva Duran-Nebreda

The article describes the method of using computer-learning tools during the modeling of biological processes in the high school. The author developed web pages for online processing of the results of simulation of the genetic structure of…

Computers and Society · Computer Science 2018-12-04 Olena V. Komarova

Ecology and evolution are inseparable. Motivated by some recent experiments, we have developed models of evolutionary ecology from the perspective of dynamic networks. In these models, in addition to the intra-node dynamics, which…

Populations and Evolution · Quantitative Biology 2009-11-10 Debashish Chowdhury , Dietrich Stauffer

Growing interest in modelling complex systems from brains to societies to cities using networks has led to increased efforts to describe generative processes that explain those networks. Recent successes in machine learning have prompted…

Neural and Evolutionary Computing · Computer Science 2024-01-12 Govind Gandhi

The editing of transcribed RNA by other molecules such that the form of the final product differs from that specified in the corresponding DNA sequence is ubiquitous. This paper uses an abstract, tunable Boolean genetic regulatory network…

Neural and Evolutionary Computing · Computer Science 2015-05-11 Larry Bull

The use of evolutionary methods in design and art is increasing in diversity and popularity. Approaches to using these methods for creative production typically focus either on optimisation or exploration. In this paper we introduce an…

Neural and Evolutionary Computing · Computer Science 2021-02-12 Camilo Cruz Gambardella , Jon McCormack
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