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Synthetic Biology, Artificial Intelligence, and Quantum Computing [chapter]

Rajendra K. Bera
2019 Genetic Engineering Technology and Synthetic Biology [Working Title]  
We envisage a world where genetic engineering, artificial intelligence (AI), and quantum computing (QC) will coalesce to bring about a forced speciation of the Homo sapiens.  ...  The day is perhaps not far off when Homo sapiens itself will initiate its own speciation once it advances synthetic biology to a level where it can safely modify the brain to temper emotion and enhance  ...  Synthetic Biology, Artificial Intelligence, and Quantum Computing DOI: Synthetic Biology, Artificial Intelligence, and Quantum Computing DOI:  ... 
doi:10.5772/intechopen.83434 fatcat:5kgm2k2qe5amrnggyzjk4qlmi4

Synthetic Biology and Artificial Intelligence: Grounding a Cross-Disciplinary Approach to the Synthetic Exploration of (Embodied) Cognition

Luisa Damiano, Pasquale Stano
2018 Complex Systems  
Recent scientific developments-the emergence in the 1990s of a "bodycentered" artificial intelligence (AI) and the birth in the 2000s of synthetic biology (SB)-allow and require the constitution of a new  ...  and to the full realization of the "embodiment turn" in contemporary AI.  ...  This work has been stimulated by our involvement in the European COST Action CM-1304 "Emergence and Evolution of Complex Chemical Systems" and TD-1308 "Origins and evolution of life on Earth and in the  ... 
doi:10.25088/complexsystems.27.3.199 fatcat:m5fgx3cannbtlaaxq7ukiku3ci

Biomedical Signal Processing, Artificial Neural Network: A Review

Chhatrapal Singh, Jaspinder Singh
2016 Indian Journal of Science and Technology  
Neural networks are used in lot of areas of industry like finance, engineering, biology. Here describes the ANN and its importance.  ...  This paper shows some basic features and processing techniques for biomedical signals and also contains the brief description of neural networks.  ...  The characteristic of artificial neural networks are very similar to an intelligent system and other artificial intelligence based applications 6 .  ... 
doi:10.17485/ijst/2015/v8i1/106889 fatcat:j7egzng2bjefnkrihleg5ou7wq

Parallel clustering algorithms

Xiaobo Li, Zhixi Fang
1989 Parallel Computing  
Therefore, the parallelization of clustering algorithms is inevitable, and various parallel clustering algorithms have been implemented and applied to many applications.  ...  Therefore, the applications of parallel clustering algorithms and the clustering algorithms for parallel computations are described in this paper.  ...  For example, as in the engineering field including machine learning, artificial intelligence, pattern recognition, mechanical engineering and electrical engineering; computer science researches of web  ... 
doi:10.1016/0167-8191(89)90036-7 fatcat:uly53om5cjgzvcfdft5mkikafe

A Review on Community Detection in Large Complex Networks from Conventional to Deep Learning Methods: A Call for the Use of Parallel Meta-Heuristic Algorithms

Mohammed Al-Andoli, Shing Chiang Tan, Wooi Ping Cheah, Sin Yin Tan
2021 IEEE Access  
SYNTHETIC DATASETS Synthetic dataset is artificially produced rather than collected from real events.  ...  Deep learning (hereinafter referred to as DL) has become one of the most active research areas in artificial intelligence and machine learning.  ... 
doi:10.1109/access.2021.3095335 fatcat:4zggvxofqvbcjbwylk7swc3c34

Proposed Collective ICOM-based post-scarcity/post-capital networked communities

S. Mason Dambrot
2021 Procedia Computer Science  
operate as a unique intuitive human-analogous Collective Artificial General Intelligence (cAGI), designed to share continuous multiple human interactions as a controlled testbed for shared collaborative  ...  operate as a unique intuitive human-analogous Collective Artificial General Intelligence (cAGI), designed to share continuous multiple human interactions as a controlled testbed for shared collaborative  ...  Funding and Investing Note that the trends above could potentially be addressed through funding of scientific research and investing in technology: • Advances in synthetic biology, synthetic genomics and  ... 
doi:10.1016/j.procs.2021.06.019 fatcat:rqrhgb44hbdxthkm64zp2xwxci

Towards Programming Adaptive Linear Neural Networks Through Chemical Reaction Networks [article]

Yuzhen Fan, Xiaoyu Zhang, Chuanhou Gao
2022 arXiv   pre-print
The results will have potential implications for the developments of synthetic biology, molecular computer and artificial intelligence.  ...  This paper is concerned with programming adaptive linear neural networks (ALNNs) using chemical reaction networks (CRNs) equipped with mass-action kinetics.  ...  programming paradigms. (3) Artificial intelligence (AI).  ... 
arXiv:2204.03168v2 fatcat:py2npcim7rgwhae225vtt3dcc4

Macromolecular networks and intelligence in microorganisms

Hans V. Westerhoff, Aaron N. Brooks, Evangelos Simeonidis, Rodolfo García-Contreras, Fei He, Fred C. Boogerd, Victoria J. Jackson, Valeri Goncharuk, Alexey Kolodkin
2014 Frontiers in Microbiology  
biomolecular networks may enable synthetic biologists to create intelligent molecular networks for biotechnology, possibly generating new forms of intelligence, first in silico and then in vivo.  ...  Here, we explore how macromolecular networks in microbes confer intelligent characteristics, such as memory, anticipation, adaptation and reflection and we review current understanding of how network organization  ...  Many of these aspects may be useful for synthetic biology; a synthetic biology that will give rise to much more sustainable, productive systems. ACKNOWLEDGMENTS Hans V.  ... 
doi:10.3389/fmicb.2014.00379 pmid:25101076 pmcid:PMC4106424 fatcat:mm5xevb23jexrawtydiz5litdu

The Age of Analog Networks

Claudio Mattiussi, Daniel Marbach, Peter Dürr, Dario Floreano
2008 The AI Magazine  
Some examples of analog networks are genetic regulatory networks, metabolic networks, neural networks, analog electronic circuits, and control systems.  ...  In this paper we will discuss the general relevance of the analog network concept and describe an evolutionary approach to the automatic synthesis and the reverse engineering of analog networks.  ...  Acknowledgments Many thanks to Simon Harding for reading and commenting on the manuscript. This work was supported by the Swiss National Science Foundation, grant no. 200021-112060.  ... 
doi:10.1609/aimag.v29i3.2156 fatcat:nf3oitjnh5f55o56pobithegqq

The dying dreamer: architecture of parallel realities

Malin Zimm
2003 Technoetic Arts  
The investigation leads into elaborate experiments in physical space, employing and developing artificiality and virtuality, as the creative mind pursues the desire for parallel realities.  ...  The second article, "The Operative Fields of the Artificial", focuses on the negotiation of artificiality through the layers of fiction in des Esseintes´ projects and the transitional character of his  ...  Katja Grillner for generously supporting this work with ideas and criticism, and for being such a brilliant source of both knowledge and energy.  ... 
doi:10.1386/tear.1.1.61/0 fatcat:xugesaswbndnppnyd6m332d3ne

Artificial Gene Regulatory Networks—A Review

Sylvain Cussat-Blanc, Kyle Harrington, Wolfgang Banzhaf
2019 Artificial Life  
In Engineering, modeling and implementations of artificial gene regulatory 1 networks has been an expanding field of research and development over the past few decades.  ...  This review discusses the concept of gene regulation, the current state-of-the-art in gene regulatory networks, including modeling and simulation, and reviews their use in artificial evolutionary settings  ...  more intelligent behaviors for artificial agents in the near future.  ... 
doi:10.1162/artl_a_00267 fatcat:kmshnduj7bap5nezctik63uvae

A Unifying Mathematical Framework for Genetic Robustness, Environmental Robustness, Network Robustness and their Trade-offs on Phenotype Robustness in Biological Networks. Part III: Synthetic Gene Networks in Synthetic Biology

Bor-Sen Chen, Ying-Po Lin
2013 Evolutionary Bioinformatics  
This paper presents a unifying mathematical framework for investigating the principles of both robust stabilization and environmental disturbance attenuation for synthetic gene networks in synthetic biology  ...  Therefore, the trade-offs between intrinsic robustness, genetic robustness, environmental robustness, and network robustness in synthetic biology can also be investigated through corresponding phenotype  ...  and artificial systems.  ... 
doi:10.4137/ebo.s10686 pmid:23515190 pmcid:PMC3596975 fatcat:ynwf3dstgzh4vnj3mo5h6fx25i

SCNN: Swarm Characteristic Neural Network [article]

Ha-Thanh Nguyen, Le-Minh Nguyen
2021 arXiv   pre-print
In this paper, we propose and verify the effectiveness and efficiency of SCNN, an innovative neural network inspired by the swarm concept.  ...  There is a weighted connection between nodes in a neural network. Instead of biology signals as weights for connection, the artificial neural network uses a numerical value.  ...  BACKGROUND SWARM INTELLIGENCE Swarm intelligence is a field of artificial intelligence that is motivated by the conduct of some social living creatures, for example, ants, termites, birds, and fish.  ... 
arXiv:2103.15550v1 fatcat:wdqapff7zfgzvdguzt3uvqjlyi

Evolutionary algorithms in genetic regulatory networks model [article]

Khalid Raza, Rafat Parveen
2012 arXiv   pre-print
Genetic Regulatory Networks (GRNs) plays a vital role in the understanding of complex biological processes.  ...  In this paper we have reviewed various evolutionary algorithms-based approach for modeling GRNs and discussed various opportunities and challenges.  ...  The proposed model was tested on five synthetic networks and results were compared with dynamic Bayesian network model and found that sensitivity is approximately 5% higher and precision was approximately  ... 
arXiv:1205.1986v1 fatcat:sndsoua6cfbftpru4iv5jkxm6q

Fundamentals of Neural Networks

Amey Thakur
2021 International Journal for Research in Applied Science and Engineering Technology  
Artificial Neural Networks (ANNs) are algorithm-based systems that are modelled after Biological Neural Networks (BNNs).  ...  We study neural networks (NNs) and highlight the different learning approaches and algorithms used in Machine Learning and Deep Learning.  ...  NEURAL NETWORKS AND ARTIFICIAL INTELLIGENCE In certain quarters, neural networks are synonymous with artificial intelligence.  ... 
doi:10.22214/ijraset.2021.37362 fatcat:2ebyvnxsj5djbewbd4ii4ubl4y
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