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How small are building blocks of complex networks [article]

Almerima Jamakovic, Priya Mahadevan, Amin Vahdat, Marian Boguna, Dmitri Krioukov
2015 arXiv   pre-print
Network motifs are small building blocks of complex networks. Statistically significant motifs often perform network-specific functions.  ...  This finding impacts methods relying on motif statistical significance, and enriches our understanding of the elementary forces that shape the structure of complex networks.  ...  INTRODUCTION A promising direction in the study of the structure and function of complex networks is to identify their building blocks, or motifs [1] [2] [3] , which are small subgraphs in a real network  ... 
arXiv:0908.1143v2 fatcat:oxuz34vqqrayzk7zum4t36lg7y

Integrative systems and synthetic biology of cell-matrix adhesion sites

Eli Zamir
2016 Cell Adhesion & Migration  
The complexity of cell-matrix adhesion convolves its roles in the development and functioning of multicellular organisms and their evolutionary tinkering.  ...  In this review I discuss some of the fundamental questions in systems biology of cell-matrix adhesion and how synthetic biology can help addressing them.  ...  Acknowledgments Dedicated to the memory of Uri Zamir.  ... 
doi:10.1080/19336918.2016.1148865 pmid:26853318 pmcid:PMC5079407 fatcat:ylrdjjdhtng2xiaakrpvt62vya

Worldwide Detection of Informal Settlements via Topological Analysis of Crowdsourced Digital Maps

Satej Soman, Anni Beukes, Cooper Nederhood, Nicholas Marchio, Luís M.A. Bettencourt
2020 ISPRS International Journal of Geo-Information  
We illustrate how the lack of physical accessibility can be identified in detail, how the complexity and costs of solutions can be assessed and how detailed spatial proposals are generated.  ...  We analyze 1 terabyte of OpenStreetMap (OSM) crowdsourced data to create worldwide indices of street block accessibility and local cadastral maps and propose infrastructure extensions with a focus on 120  ...  Birali Runesha of the University of Chicago Research Computing Center (RCC) for technical assistance in parallelization and computation.  ... 
doi:10.3390/ijgi9110685 fatcat:3tpwayfibvhelk6q7dprer5vnm

Multicast three-stage Clos networks

Guido Maier, Achille Pattavina
2010 Computer Communications  
The non-blocking conditions for this network are reported here and discussed.  ...  An evaluation is carried out in order to show how the network complexity depends on the main network and traffic parameters, that is the switching matrix sizes and the type of multicast traffic.  ...  Acknowledgements The work described in this paper was carried out with the support of the BONE-project (''Building the Future Optical Network in Europe"), a Network of Excellence funded by the European  ... 
doi:10.1016/j.comcom.2010.01.022 fatcat:cwvt6qpu3jcojjf7wfcje644by

Emerging Principles Governing the Operation of Neural Networks

P A Getting
1989 Annual Review of Neuroscience  
Finding out how neural networks are organized and understanding what com putational principles underlie their operation remain challenges to modern neuroscience.  ...  INTRODUCTION A basic tenet of neuroscience is that the ability of the brain to produce complex behaviors such as sensory perception or motor control arises from the interconnection of neurons into networks  ...  I am supported by National Institutes of Health grants NS 17328, NS 15350, and HL32336.  ... 
doi:10.1146/ pmid:2648949 fatcat:6yt2irz7tza5fa3lwah2rgye3u

Emerging Principles Governing The Operation Of Neural Networks

P. Getting
1989 Annual Review of Neuroscience  
Finding out how neural networks are organized and understanding what com putational principles underlie their operation remain challenges to modern neuroscience.  ...  INTRODUCTION A basic tenet of neuroscience is that the ability of the brain to produce complex behaviors such as sensory perception or motor control arises from the interconnection of neurons into networks  ...  I am supported by National Institutes of Health grants NS 17328, NS 15350, and HL32336.  ... 
doi:10.1146/annurev.neuro.12.1.185 fatcat:6olgptq35jgcxocbfspbnvxdqu

Theorizing benefits and constraints in collaborative environmental governance: a transdisciplinary social-ecological network approach for empirical investigations

Örjan Bodin, Garry Robins, Ryan R. J. McAllister, Angela M. Guerrero, Beatrice Crona, Maria Tengö, Mark Lubell
2016 Ecology and Society  
The effectiveness of such arrangements, however, depends on how well any ecological interdependencies across governed ecosystems are aligned with patterns of collaboration.  ...  We argue for the development of empirically informed theories, which are not only able to transcend disciplinary boundaries, but are also explicit in taking these complex social-ecological interdependences  ...  These SES building blocks only constitute a small subset of all theoretically possible building blocks.  ... 
doi:10.5751/es-08368-210140 fatcat:7brqckv5o5dr3mfs2v5evnasje

The assembly and disassembly of ecological networks

J. Bascompte, D. B. Stouffer
2009 Philosophical Transactions of the Royal Society of London. Biological Sciences  
First, we focus on network assembly by emphasizing temporal processes at the species level, as well as the structural building blocks of complex ecological networks.  ...  This process of network collapse may indeed be related to the process of network build-up, although very little is known about both processes and even less about their relationship.  ...  This work was funded by the European Heads of Research Councils, the European Science Foundation and the EC Sixth Framework Programme through a EURYI (European Young Investigator) award (to J.B.) and a  ... 
doi:10.1098/rstb.2008.0226 pmid:19451127 pmcid:PMC2685423 fatcat:75g26h7bffbllitfvkcwxvnuyy

IamNN: Iterative and Adaptive Mobile Neural Network for Efficient Image Classification [article]

Sam Leroux, Pavlo Molchanov, Pieter Simoens, Bart Dhoedt, Thomas Breuel, Jan Kautz
2018 arXiv   pre-print
The resulting network is much smaller than the original network and can adapt the computational cost to the complexity of the input image.  ...  The core idea of ResNets is to have shortcut connections between layers that allow the network to be much deeper while still being easy to optimize avoiding vanishing gradients.  ...  Figure 2 2 shows how many iterations are used for each block in the ImageNet network.  ... 
arXiv:1804.10123v1 fatcat:vkls76zzmjar3mfmufnxo53epi

The Build-Up of Diversity in Complex Ecosystems [article]

Andrea Tacchella, Riccardo Di Clemente, Andrea Gabrielli, Luciano Pietronero
2016 arXiv   pre-print
We base our reasoning on the combinatoric picture that the nodes on one layer of these bipartite networks can be described as combinations of a number of fundamental building blocks.  ...  We show that if the usefulness of the building blocks has a scale-free distribution, then maximally entropic baskets of building blocks will give rise to very rich behaviors.  ...  What is left to define are the properties of the topology of the bipartite network of building blocks and combinations.  ... 
arXiv:1609.03617v1 fatcat:zrjgdxzylbhyzlqutbvye4tw2m

Grip on complexity in chemical reaction networks

Albert S Y Wong, Wilhelm T S Huck
2017 Beilstein Journal of Organic Chemistry  
To truly understand how living systems function, we need a complete understanding of how chemical reaction networks (CRNs) create function.  ...  Living systems rely on complex networks of chemical reactions to control the concentration of molecules in space and time.  ...  Network motifs are dynamic building blocks Network motifs, like bistable switches and oscillators, form the basic building blocks of dynamic behavior.  ... 
doi:10.3762/bjoc.13.147 pmid:28845192 pmcid:PMC5550812 fatcat:6d23zyutwfdynodydf44jazu6y

Global Resource Distribution: Allocation of Actin Building Blocks by Profilin

Jessica L. Henty-Ridilla, Bruce L. Goode
2015 Developmental Cell  
Complementary studies from Suarez et al. (2015) and Rotty et al. (2015) now show that profilin controls the partitioning of actin monomers between competing actin networks assembled by Arp2/3 complex and  ...  How cells regulate the distribution of a limited pool of actin between two competing structures has long been a mystery.  ...  ACKNOWLEDGMENTS This research was supported by a fellowship from the Leukemia and Lymphoma Society to J.L.H-R and a grant from the National Institutes of Health (GM083137) to B.L.G.  ... 
doi:10.1016/j.devcel.2014.12.022 pmid:25584793 fatcat:rv7m5uff65h2ja6eyk2uhcxpf4

Deep Learning for Multi-Tissue Cancer Classification of Gene Expressions (GeneXNet)

Tarek Khorshed, Mohamed N. Moustafa, Ahmed Rafea
2020 IEEE Access  
We introduce a new Convolutional Neural Network architecture called Gene eXpression Network (GeneXNet), which is specifically designed to address the complex nature of gene expressions.  ...  We demonstrate how our model can be used for transfer learning to build classifiers for tumors lacking sufficient samples to be trained independently.  ...  Our network is designed to specifically address the complex nature of gene expressions and addresses the lack of training samples by incorporating multiple layers of building blocks which we refer to as  ... 
doi:10.1109/access.2020.2992907 fatcat:tn4x7uiprrchvcvj2veylaqaoy

Akid: A Library for Neural Network Research and Production from a Dataism Approach [article]

Shuai Li
2017 arXiv   pre-print
Neural networks are a revolutionary but immature technique that is fast evolving and heavily relies on data.  ...  At the top application stack, it provides out-of-box tools for neural network applications. Lower down, akid provides a programming paradigm that lets user easily build customized models.  ...  Here we show how to build an arbitrary acyclic graph of blocks using class Brain, to illustrate how to use blocks in akid.  ... 
arXiv:1701.00609v1 fatcat:zhxcma62ffhxfnacuaw3dwpzcy

Effective Building Block Design for Deep Convolutional Neural Networks using Search [article]

Jayanta K Dutta, Jiayi Liu, Unmesh Kurup, Mohak Shah
2018 arXiv   pre-print
Deep learning has shown promising results on many machine learning tasks but DL models are often complex networks with large number of neurons and layers, and recently, complex layer structures known as  ...  building blocks.  ...  In effect we constrain our search to small networks of repeatable blocks instead of arbitrarily deep networks with unconstrained layer sizes.  ... 
arXiv:1801.08577v1 fatcat:mtzqyqfyunck5mbwe6l3pyzoau
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