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Book ; Online: Calculating lexicase selection probabilities is NP-Hard

Dolson, Emily

2023

Abstract: Calculating the probability of an individual solution being selected under lexicase selection is an important problem in attempts to develop a deeper theoretical understanding of lexicase selection, a state-of-the art parent selection algorithm in ... ...

Abstract	Calculating the probability of an individual solution being selected under lexicase selection is an important problem in attempts to develop a deeper theoretical understanding of lexicase selection, a state-of-the art parent selection algorithm in evolutionary computation. Discovering a fast solution to this problem would also have implications for efforts to develop practical improvements to lexicase selection. Here, I prove that this problem, which I name lex-prob, is NP-Hard. I achieve this proof by reducing SAT, a well-known NP-Complete problem, to lex-prob in polynomial time. This reduction involves an intermediate step in which a popular variant of lexicase selection, epsilon-lexicase selection, is reduced to standard lexicase selection. This proof has important practical implications for anyone needing a fast way of calculating the probabilities of individual solutions being selected under lexicase selection. Doing so in polynomial time would be incredibly challenging, if not all-together impossible. Thus, finding approximation algorithms or practical optimizations for speeding up the brute-force solution is likely more worthwhile. This result also has deeper theoretical implications about the relationship between epsilon-lexicase selection and lexicase selection and the relationship between lex-prob and other NP-Hard problems.
Keywords	Computer Science - Neural and Evolutionary Computing ; Computer Science - Computational Complexity ; F.2
Subject code	519
Publishing date	2023-01-17
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Artificial selection methods from evolutionary computing show promise for directed evolution of microbes.

Lalejini, Alexander / Dolson, Emily / Vostinar, Anya E / Zaman, Luis

eLife

2022 Volume 11

Abstract: Directed microbial evolution harnesses evolutionary processes in the laboratory to construct microorganisms with enhanced or novel functional traits. Attempting to direct evolutionary processes for applied goals is fundamental to evolutionary computation, ...

Abstract	Directed microbial evolution harnesses evolutionary processes in the laboratory to construct microorganisms with enhanced or novel functional traits. Attempting to direct evolutionary processes for applied goals is fundamental to evolutionary computation, which harnesses the principles of Darwinian evolution as a general-purpose search engine for solutions to challenging computational problems. Despite their overlapping approaches, artificial selection methods from evolutionary computing are not commonly applied to living systems in the laboratory. In this work, we ask whether parent selection algorithms-procedures for choosing promising progenitors-from evolutionary computation might be useful for directing the evolution of microbial populations when selecting for multiple functional traits. To do so, we introduce an agent-based model of directed microbial evolution, which we used to evaluate how well three selection algorithms from evolutionary computing (tournament selection, lexicase selection, and non-dominated elite selection) performed relative to methods commonly used in the laboratory (elite and top 10% selection). We found that multiobjective selection techniques from evolutionary computing (lexicase and non-dominated elite) generally outperformed the commonly used directed evolution approaches when selecting for multiple traits of interest. Our results motivate ongoing work transferring these multiobjective selection procedures into the laboratory and a continued evaluation of more sophisticated artificial selection methods.
MeSH term(s)	Algorithms ; Biological Evolution ; Phenotype ; Search Engine
Language	English
Publishing date	2022-08-02
Publishing country	England
Document type	Journal Article ; Research Support, U.S. Gov't, Non-P.H.S.
ZDB-ID	2687154-3
ISSN	2050-084X ; 2050-084X
ISSN (online)	2050-084X
ISSN	2050-084X
DOI	10.7554/eLife.79665
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: The ecology-evolution continuum and the origin of life.

Baum, David A / Peng, Zhen / Dolson, Emily / Smith, Eric / Plum, Alex M / Gagrani, Praful

Journal of the Royal Society, Interface

2023 Volume 20, Issue 208, Page(s) 20230346

Abstract: Prior research on evolutionary mechanisms during the origin of life has mainly assumed the existence of populations of discrete entities with information encoded in genetic polymers. Recent theoretical advances in autocatalytic chemical ecology establish ...

Abstract	Prior research on evolutionary mechanisms during the origin of life has mainly assumed the existence of populations of discrete entities with information encoded in genetic polymers. Recent theoretical advances in autocatalytic chemical ecology establish a broader evolutionary framework that allows for adaptive complexification prior to the emergence of bounded individuals or genetic encoding. This framework establishes the formal equivalence of cells, ecosystems and certain localized chemical reaction systems as autocatalytic chemical ecosystems (ACEs): food-driven (open) systems that can grow due to the action of autocatalytic cycles (ACs). When ACEs are organized in meta-ecosystems, whether they be populations of cells or sets of chemically similar environmental patches, evolution, defined as change in AC frequency over time, can occur. In cases where ACs are enriched because they enhance ACE persistence or dispersal ability, evolution is adaptive and can build complexity. In particular, adaptive evolution can explain the emergence of self-bounded units (e.g. protocells) and genetic inheritance mechanisms. Recognizing the continuity between ecological and evolutionary change through the lens of autocatalytic chemical ecology suggests that the origin of life should be seen as a general and predictable outcome of driven chemical ecosystems rather than a phenomenon requiring specific, rare conditions.
MeSH term(s)	Humans ; Origin of Life ; Ecosystem ; Catalysis ; Artificial Cells
Language	English
Publishing date	2023-11-01
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2156283-0
ISSN	1742-5662 ; 1742-5689
ISSN (online)	1742-5662
ISSN	1742-5689
DOI	10.1098/rsif.2023.0346
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Book ; Online: Phylogeny-informed fitness estimation

Lalejini, Alexander / Moreno, Matthew Andres / Hernandez, Jose Guadalupe / Dolson, Emily

2023

Abstract: Phylogenies (ancestry trees) depict the evolutionary history of an evolving population. In evolutionary computing, a phylogeny can reveal how an evolutionary algorithm steers a population through a search space, illuminating the step-by-step process by ... ...

Abstract	Phylogenies (ancestry trees) depict the evolutionary history of an evolving population. In evolutionary computing, a phylogeny can reveal how an evolutionary algorithm steers a population through a search space, illuminating the step-by-step process by which any solutions evolve. Thus far, phylogenetic analyses have primarily been applied as post-hoc analyses used to deepen our understanding of existing evolutionary algorithms. Here, we investigate whether phylogenetic analyses can be used at runtime to augment parent selection procedures during an evolutionary search. Specifically, we propose phylogeny-informed fitness estimation, which exploits a population's phylogeny to estimate fitness evaluations. We evaluate phylogeny-informed fitness estimation in the context of the down-sampled lexicase and cohort lexicase selection algorithms on two diagnostic analyses and four genetic programming (GP) problems. Our results indicate that phylogeny-informed fitness estimation can mitigate the drawbacks of down-sampled lexicase, improving diversity maintenance and search space exploration. However, the extent to which phylogeny-informed fitness estimation improves problem-solving success for GP varies by problem, subsampling method, and subsampling level. This work serves as an initial step toward improving evolutionary algorithms by exploiting runtime phylogenetic analysis. Comment: Submitted as contribution to GPTP XX
Keywords	Computer Science - Neural and Evolutionary Computing
Subject code	006
Publishing date	2023-06-06
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Interpreting the Tape of Life: Ancestry-Based Analyses Provide Insights and Intuition about Evolutionary Dynamics.

Dolson, Emily / Lalejini, Alexander / Jorgensen, Steven / Ofria, Charles

Artificial life

2020 Volume 26, Issue 1, Page(s) 58–79

Abstract: Fine-scale evolutionary dynamics can be challenging to tease out when focused on the broad brush strokes of whole populations over long time spans. We propose a suite of diagnostic analysis techniques that operate on lineages and phylogenies in digital ... ...

Abstract	Fine-scale evolutionary dynamics can be challenging to tease out when focused on the broad brush strokes of whole populations over long time spans. We propose a suite of diagnostic analysis techniques that operate on lineages and phylogenies in digital evolution experiments, with the aim of improving our capacity to quantitatively explore the nuances of evolutionary histories in digital evolution experiments. We present three types of lineage measurements: lineage length, mutation accumulation, and phenotypic volatility. Additionally, we suggest the adoption of four phylogeny measurements from biology: phylogenetic richness, phylogenetic divergence, phylogenetic regularity, and depth of the most-recent common ancestor. In addition to quantitative metrics, we also discuss several existing data visualizations that are useful for understanding lineages and phylogenies: state sequence visualizations, fitness landscape overlays, phylogenetic trees, and Muller plots. We examine the behavior of these metrics (with the aid of data visualizations) in two well-studied computational contexts: (1) a set of two-dimensional, real-valued optimization problems under a range of mutation rates and selection strengths, and (2) a set of qualitatively different environments in the Avida digital evolution platform. These results confirm our intuition about how these metrics respond to various evolutionary conditions and indicate their broad value.
MeSH term(s)	Biodiversity ; Biological Evolution ; Computational Biology ; Computer Simulation ; Environment ; Evolution, Molecular ; Life ; Mutation ; Phylogeny ; Selection, Genetic
Language	English
Publishing date	2020-02-06
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't ; Research Support, U.S. Gov't, Non-P.H.S.
ZDB-ID	2024100-8
ISSN	1530-9185 ; 1064-5462
ISSN (online)	1530-9185
ISSN	1064-5462
DOI	10.1162/artl_a_00313
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Book ; Online: What can phylogenetic metrics tell us about useful diversity in evolutionary algorithms?

Hernandez, Jose Guadalupe / Lalejini, Alexander / Dolson, Emily

2021

Abstract: It is generally accepted that "diversity" is associated with success in evolutionary algorithms. However, diversity is a broad concept that can be measured and defined in a multitude of ways. To date, most evolutionary computation research has measured ... ...

Abstract	It is generally accepted that "diversity" is associated with success in evolutionary algorithms. However, diversity is a broad concept that can be measured and defined in a multitude of ways. To date, most evolutionary computation research has measured diversity using the richness and/or evenness of a particular genotypic or phenotypic property. While these metrics are informative, we hypothesize that other diversity metrics are more strongly predictive of success. Phylogenetic diversity metrics are a class of metrics popularly used in biology, which take into account the evolutionary history of a population. Here, we investigate the extent to which 1) these metrics provide different information than those traditionally used in evolutionary computation, and 2) these metrics better predict the long-term success of a run of evolutionary computation. We find that, in most cases, phylogenetic metrics behave meaningfully differently from other diversity metrics. Moreover, our results suggest that phylogenetic diversity is indeed a better predictor of success. Comment: 21 page, 7 figures. Presented Genetic Programming in Theory and Practice, 2021
Keywords	Computer Science - Neural and Evolutionary Computing ; Quantitative Biology - Populations and Evolution ; I.2.2
Subject code	006
Publishing date	2021-08-28
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: The MODES Toolbox: Measurements of Open-Ended Dynamics in Evolving Systems.

Dolson, Emily L / Vostinar, Anya E / Wiser, Michael J / Ofria, Charles

Artificial life

2019 Volume 25, Issue 1, Page(s) 50–73

Abstract: Building more open-ended evolutionary systems can simultaneously advance our understanding of biology, artificial life, and evolutionary computation. In order to do so, however, we need a way to determine when we are moving closer to this goal. We ... ...

Abstract	Building more open-ended evolutionary systems can simultaneously advance our understanding of biology, artificial life, and evolutionary computation. In order to do so, however, we need a way to determine when we are moving closer to this goal. We propose a set of metrics that allow us to measure a system's ability to produce commonly-agreed-upon hallmarks of open-ended evolution: change potential, novelty potential, complexity potential, and ecological potential. Our goal is to make these metrics easy to incorporate into a system, and comparable across systems so that we can make coherent progress as a field. To this end, we provide detailed algorithms (including C++ implementations) for these metrics that should be easy to incorporate into existing artificial life systems. Furthermore, we expect this toolbox to continue to grow as researchers implement these metrics in new languages and as the community reaches consensus about additional hallmarks of open-ended evolution. For example, we would welcome a measurement of a system's potential to produce major transitions in individuality. To confirm that our metrics accurately measure the hallmarks we are interested in, we test them on two very different experimental systems: NK landscapes and the Avida digital evolution platform. We find that our observed results are consistent with our prior knowledge about these systems, suggesting that our proposed metrics are effective and should generalize to other systems.
MeSH term(s)	Algorithms ; Biological Evolution ; Models, Biological ; Synthetic Biology
Language	English
Publishing date	2019-05-09
Publishing country	United States
Document type	Journal Article ; Research Support, U.S. Gov't, Non-P.H.S.
ZDB-ID	2024100-8
ISSN	1530-9185 ; 1064-5462
ISSN (online)	1530-9185
ISSN	1064-5462
DOI	10.1162/artl_a_00280
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Article ; Online: UV-C tower for point-of-care decontamination of filtering facepiece respirators.

Kayani, Badar J / Weaver, Davis T / Gopalakrishnan, Vishhvaan / King, Eshan S / Dolson, Emily / Krishnan, Nikhil / Pelesko, Julia / Scott, Michael J / Hitomi, Masahiro / Cadnum, Jennifer L / Li, Daniel F / Donskey, Curtis J / Scott, Jacob G / Charnas, Ian

American journal of infection control

2020 Volume 49, Issue 4, Page(s) 424–429

Abstract: Background: Filtering facepiece respirators (FFR) are critical for protecting essential personnel and limiting the spread of disease. Due to the current COVID-19 pandemic, FFR supplies are dwindling in many health systems, necessitating re-use of ... ...

Abstract	Background: Filtering facepiece respirators (FFR) are critical for protecting essential personnel and limiting the spread of disease. Due to the current COVID-19 pandemic, FFR supplies are dwindling in many health systems, necessitating re-use of potentially contaminated FFR. Multiple decontamination solutions have been developed to meet this pressing need, including systems designed for bulk decontamination of FFR using vaporous hydrogen peroxide or ultraviolet-C (UV-C) radiation. However, the large scale on which these devices operate may not be logistically practical for small or rural health care settings or for ad hoc use at points-of-care. Methods: Here, we present the Synchronous UV Decontamination System, a novel device for rapidly deployable, point-of-care decontamination using UV-C germicidal irradiation. We designed a compact, easy-to-use device capable of delivering over 2 J cm2 of UV-C radiation in one minute. Results: We experimentally tested Synchronous UV Decontamination System' microbicidal capacity and found that it eliminates near all virus from the surface of tested FFRs, with less efficacy against pathogens embedded in the inner layers of the masks. Conclusions: This short decontamination time should enable care-providers to incorporate decontamination of FFR into a normal donning and doffing routine following patient encounters.
MeSH term(s)	COVID-19/prevention & control ; COVID-19/virology ; Decontamination/instrumentation ; Decontamination/methods ; Equipment Reuse ; Humans ; Point-of-Care Systems ; Respiratory Protective Devices/virology ; SARS-CoV-2 ; Ultraviolet Rays
Keywords	covid19
Language	English
Publishing date	2020-11-10
Publishing country	United States
Document type	Journal Article
ZDB-ID	392362-9
ISSN	1527-3296 ; 0196-6553
ISSN (online)	1527-3296
ISSN	0196-6553
DOI	10.1016/j.ajic.2020.11.010
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Article: UV-C Tower for point-of-care decontamination of filtering facepiece respirators

Kayani, Badar J / Weaver, Davis T / Gopalakrishnan, Vishvaan / King, Eshan S / Dolson, Emily / Krishnan, Nikhil / Pelesko, Julia / Scott, Michael J / Hitomi, Masahiro / Cadnum, Jennifer L / Li, Daniel F / Donskey, Curtis J / Scott, Jacob G / Charnas, Ian

Am. j. infect. control

Abstract: Filtering facepiece respirators (FFR) are critical for protecting essential personnel and limiting the spread of disease. Due to the current COVID-19 pandemic, FFR supplies are dwindling in many health systems, necessitating re-use of potentially ... ...

Abstract	Filtering facepiece respirators (FFR) are critical for protecting essential personnel and limiting the spread of disease. Due to the current COVID-19 pandemic, FFR supplies are dwindling in many health systems, necessitating re-use of potentially contaminated FFR. Multiple decontamination solutions have been developed to meet this pressing need, including systems designed for bulk decontamination of FFR using vaprous hydrogen peroxide or UV-C radiation. However, the large scale on which these devices operate may not be logistically practical for small or rural health care settings or for ad hoc use at points-of-care. Here, we present the Synchronous UV Decontamination System (SUDS), a novel device for rapidly deployable, point-of-care decontamination using UV-C germicidal irradiation. We designed a compact, easy-to-use device capable of delivering over 2 J_ cm2 of UV-C radiation in one minute. We experimentally tested SUDS' microbicidal capacity and found that it eliminates near all virus from the surface of tested FFRs, with less efficacy against pathogens embedded in the inner layers of the masks. This short decontamination time should enable care-providers to incorporate decontamination of FFR into a normal donning and doffing routine following patient encounters.
Keywords	covid19
Publisher	WHO
Document type	Article
Note	WHO #Covidence: #917197
Database	COVID19

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Book ; Online: Controlling the speed and trajectory of evolution with counterdiabatic driving

Iram, Shamreen / Dolson, Emily / Chiel, Joshua / Pelesko, Julia / Krishnan, Nikhil / Güngör, Özenç / Kuznets-Speck, Benjamin / Deffner, Sebastian / Ilker, Efe / Scott, Jacob G. / Hinczewski, Michael

2019

Abstract: The pace and unpredictability of evolution are critically relevant in a variety of modern challenges: combating drug resistance in pathogens and cancer, understanding how species respond to environmental perturbations like climate change, and developing ... ...

Abstract	The pace and unpredictability of evolution are critically relevant in a variety of modern challenges: combating drug resistance in pathogens and cancer, understanding how species respond to environmental perturbations like climate change, and developing artificial selection approaches for agriculture. Great progress has been made in quantitative modeling of evolution using fitness landscapes, allowing a degree of prediction for future evolutionary histories. Yet fine-grained control of the speed and the distributions of these trajectories remains elusive. We propose an approach to achieve this using ideas originally developed in a completely different context: counterdiabatic driving to control the behavior of quantum states for applications like quantum computing and manipulating ultra-cold atoms. Implementing these ideas for the first time in a biological context, we show how a set of external control parameters (i.e. varying drug concentrations / types, temperature, nutrients) can guide the probability distribution of genotypes in a population along a specified path and time interval. This level of control, allowing empirical optimization of evolutionary speed and trajectories, has myriad potential applications, from enhancing adaptive therapies for diseases, to the development of thermotolerant crops in preparation for climate change, to accelerating bioengineering methods built on evolutionary models, like directed evolution of biomolecules. Comment: Main text: 19 pages, 5 figures; SI: 14 pages, 5 figures
Keywords	Condensed Matter - Statistical Mechanics ; Quantitative Biology - Populations and Evolution
Publishing date	2019-12-08
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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