10 results match your criteria: "3 Santa Fe Institute[Affiliation]"
Philos Trans R Soc Lond B Biol Sci
June 2019
3 Santa Fe Institute, Hyde Park Road, Santa Fe, NM , USA.
Philos Trans R Soc Lond B Biol Sci
June 2019
3 Santa Fe Institute, 1399 Hyde Park Road, Santa Fe NM 87501 , USA.
Cognitive networks have evolved a broad range of solutions to the problem of gathering, storing and responding to information. Some of these networks are describable as static sets of neurons linked in an adaptive web of connections. These are 'solid' networks, with a well-defined and physically persistent architecture.
View Article and Find Full Text PDFPhilos Trans R Soc Lond B Biol Sci
June 2019
1 ICREA-Complex Systems Lab, Universitat Pompeu Fabra, 08003 Barcelona , Spain.
Liquid neural networks (or 'liquid brains') are a widespread class of cognitive living networks characterized by a common feature: the agents (ants or immune cells, for example) move in space. Thus, no fixed, long-term agent-agent connections are maintained, in contrast with standard neural systems. How is this class of systems capable of displaying cognitive abilities, from learning to decision-making? In this paper, the collective dynamics, memory and learning properties of liquid brains is explored under the perspective of statistical physics.
View Article and Find Full Text PDFPhilos Trans R Soc Lond B Biol Sci
June 2019
3 Santa Fe Institute, Santa Fe, NM , USA.
Brains are composed of connected neurons that compute by transmitting signals. The neurons are generally fixed in space, but the communication patterns that enable information processing change rapidly. By contrast, other biological systems, such as ant colonies, bacterial colonies, slime moulds and immune systems, process information using agents that communicate locally while moving through physical space.
View Article and Find Full Text PDFHum Biol
July 2015
2 City University London, London, United Kingdom.
In this article we explore the theoretical limits of the inference of cultural transmission modes based on sparse population-level data. We approach this problem by investigating whether different transmission modes produce different temporal dynamics of cultural change. In particular, we explore whether different transmission modes result in sufficiently different distributions of the average time a variant stays the most common variant in the population, tmax, so that their inference can be guaranteed on the basis of an estimate of tmax.
View Article and Find Full Text PDFNat Commun
March 2015
1] Graduate Biochemistry Group, Department of Biochemistry and Molecular Biophysics, Kansas State University, 336 Ackert Hall, Manhattan, Kansas 66506, USA [2] Molecular, Cellular and Developmental Biology Program, Division of Biology, Kansas State University, 338 Ackert Hall, Manhattan, Kansas 66506, USA.
Proteasome assembly is a complex process, requiring 66 subunits distributed over several subcomplexes to associate in a coordinated fashion. Ten proteasome-specific chaperones have been identified that assist in this process. For two of these, the Pba1-Pba2 dimer, it is well established that they only bind immature core particles (CPs) in vivo.
View Article and Find Full Text PDFNature
November 2014
1] Department of Genome Sciences, University of Washington, Seattle, Washington 98195, USA [2] Department of Medicine, University of Washington, Seattle, Washington 98195, USA.
The basic body plan and major physiological axes have been highly conserved during mammalian evolution, yet only a small fraction of the human genome sequence appears to be subject to evolutionary constraint. To quantify cis- versus trans-acting contributions to mammalian regulatory evolution, we performed genomic DNase I footprinting of the mouse genome across 25 cell and tissue types, collectively defining ∼8.6 million transcription factor (TF) occupancy sites at nucleotide resolution.
View Article and Find Full Text PDFSci Rep
April 2014
1] Santa Fe Institute, 1399 Hyde Park Road, Santa Fe, NM 87501, USA [2] Instituto de Biología Molecular y Celular de Plantas (CSIC-UPV), Ingeniero Fausto Elio s/n, 46022 València, Spain.
The distribution of mutational fitness effects (DMFE) is crucial to the evolutionary fate of quasispecies. In this article we analyze the effect of the DMFE on the dynamics of a large quasispecies by means of a phenotypic version of the classic Eigen's model that incorporates beneficial, neutral, deleterious, and lethal mutations. By parameterizing the model with available experimental data on the DMFE of Vesicular stomatitis virus (VSV) and Tobacco etch virus (TEV), we found that increasing mutation does not totally push the entire viral quasispecies towards deleterious or lethal regions of the phenotypic sequence space.
View Article and Find Full Text PDFSci Rep
April 2014
1] ICREA-Complex Systems Lab, Universitat Pompeu Fabra, Dr Aiguadé, 88, 08003 Barcelona, Spain [2] Institut de Biologia Evolutiva. CSIC-UPF. CMIMA-Pssg. de la Barceloneta 37-49. 08003 Barcelona, Spain [3] Santa Fe Institute, 1399 Hyde Park Road, Santa Fe, New Mexico 87501 USA.
Meaning has been left outside most theoretical approaches to information in biology. Functional responses based on an appropriate interpretation of signals have been replaced by a probabilistic description of correlations between emitted and received symbols. This assumption leads to potential paradoxes, such as the presence of a maximum information associated to a channel that creates completely wrong interpretations of the signals.
View Article and Find Full Text PDFSci Rep
February 2014
1] Department of Physics, University of Maryland, College Park, MD, USA [2] Institute for Physical Science and Technology, University of Maryland, College Park, MD, USA [3] Santa Fe Institute, Santa Fe, NM.
Gene annotation databases (compendiums maintained by the scientific community that describe the biological functions performed by individual genes) are commonly used to evaluate the functional properties of experimentally derived gene sets. Overlap statistics, such as Fishers Exact test (FET), are often employed to assess these associations, but don't account for non-uniformity in the number of genes annotated to individual functions or the number of functions associated with individual genes. We find FET is strongly biased toward over-estimating overlap significance if a gene set has an unusually high number of annotations.
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