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opencc-zeroNov 2020View details →

Systemic paralogy and function of retinal determination network homologs in arachnids

Arachnids are important components of cave ecosystems and display many examples of troglomorphisms, such as blindness, depigmentation, and elongate appendages. Little is known about how the eyes of arachnids are specified genetically, let alone the mechanisms for eye reduction and loss in troglomorphic arachnids. Additionally, paralogy of Retinal Determination Gene Network (RDGN) homologs in spiders has convoluted functional inferences extrapolated from single-copy homologs in pancrustacean models. Here, we investigated a sister species pair of Israeli cave whip spiders (Arachnopulmonata, Amblypygi, Charinus) of which one species has reduced eyes. We generated the first embryonic transcriptomes for Amblypygi, and discovered that several RDGN homologs exhibit duplications. We show that paralogy of RDGN homologs is systemic across arachnopulmonates (arachnid orders that bear book lungs), rather than being a spider-specific phenomenon. A differential gene expression (DGE) analysis comparing the expression of RDGN genes in field-collected embryos of both species identified candidate RDGN genes involved in the formation and reduction of eyes in whip spiders. To ground bioinformatic inference of expression patterns with functional experiments, we interrogated the function of three candidate RDGN genes identified from DGE in a spider, using RNAi in the spider Parasteatoda tepidariorum. We provide functional evidence that one of these paralogs, sine oculis/Six1 A (soA), is necessary for the development of all arachnid eye types. Our results support the conservation of at least one RDGN component across Arthropoda and establish a framework for investigating the role of gene duplications in arachnid eye diversity.

opencc-zeroDec 2020View details →

Supplementary information for: Using networks to identify structure in phylogenetic tree sets

Modern phylogenomic studies produce large sets of trees that can represent variation in inferred phylogenies across genes, uncertainty in estimated phylogenies for a given gene, or both. Standard practice is to condense this variation down to a small set of point estimates or consensus trees in order to facilitate display and interpretation. However, doing so results in the loss of enormous amounts of information about the structure of the underlying tree set. Here, we propose new approaches to explore and detect structure in the tree set itself. These approaches rely on the well-developed mathematical foundations of community detection in networks and leverage two different network types. The first type uses nodes to represent trees and connects these nodes with edges whose weights are determined by the similarity (affinity) of the trees. The second type uses nodes to represent bipartitions and connects nodes with edges whose weights represent the covariance in bipartition presence/absence across trees in the set. These two network types carry information that is complementary, but not identical. A variety of methods may be applied to both networks in order to identify interesting community structure. These community detection approaches provide a rich view of the information contained in phylogenomic data sets and facilitate investigation into the forces driving inferred phylogenetic variation across genomes.

Self-stabilizing Byzantine-resilient communication in dynamic networks (video)

Full video presentation of the paper: Self-stabilizing Byzantine-resilient communication in dynamic networks. Appears in Session 1 of the 24th International Conference on Principles of Distributed Systems OPODIS 2020 <a href="https://opodis2020.unistra.fr">https://opodis2020.unistra.fr</a>

Echo-CGC: A Communication-Efficient Byzantine-tolerant Distributed Machine Learning Algorithm in Single-Hop Radio Network (video)

Full video presentation of the paper: Echo-CGC: A Communication-Efficient Byzantine-tolerant Distributed Machine Learning Algorithm in Single-Hop Radio Network. Appears in Session 2 of the 24th International Conference on Principles of Distributed Systems OPODIS 2020 <a href="https://opodis2020.unistra.fr">https://opodis2020.unistra.fr</a>

Broadcasting Competitively against Adaptive Adversary in Multi-channel Radio Networks

Full video presentation of the paper: Broadcasting Competitively against Adaptive Adversary in Multi-channel Radio Networks. Appears in Session 1 of the 24th International Conference on Principles of Distributed Systems OPODIS 2020 <a href="https://opodis2020.unistra.fr">https://opodis2020.unistra.fr</a>

Dataset for: Buffer Management for Trust Computation in Resource-constrained IoT Networks

Dataset for Buffer Management for Trust Computation in Resource-constrained IoT Networks

Effects of Network Topology On the Performance of Consensus and Distributed Learning of SVMs Using ADMM

The Alternating Direction Method Of Multipliers (ADMM) is a popular and promising distributed framework for solving large-scale machine learning problems. We consider decentralized consensus-based ADMM in which nodes may only communicate with one-hop neighbors. This may cause slow convergence. We investigate the impact of network topology on the performance of an ADMM-based learning of Support Vector Machine (SVM) using expander, and mean-degree graphs, and additionally some of the common modern network topologies. In particular, we investigate to which degree the expansion property of the network influences the convergence in terms of iterations, training and communication time. We furthermore suggest which topology is preferable. Additionally, we provide an implementation that makes these theoretical advances easily available. The results show that the performance of decentralized ADMM-based learning of SVMs in terms of convergence is improved using graphs with large spectral gaps, higher and homogeneous degrees.

Greenland ice sheet surface melt projections using artifical neural networks

Surface melt projections for the Greenland ice sheet using artificial neural networks. Organized as follows: <scenario>/<variable>/<model>/<ensemble_number>.nc

opencc-by-4.0Sep 2014View details →

HAND2 Targets Define a Network of Transcriptional Regulators that Compartmentalize the Early Limb Bud Mesenchyme

Highlights • ChIP-seq identifies the CRMs bound by endogenous HAND2 in embryos and limb buds • HAND2 controls key transcriptional regulators acting upstream of SHH in limb buds • These transcriptional circuits define proximal, anterior, and posterior identities • HAND2 establishes anterior and posterior compartments by regulating Gli3 and Tbx3

Data for "CryoDRGN: Reconstruction of heterogeneous cryo-EM structures using neural networks"

Trained models and reconstructed density maps for: <ul> <li>EMPIAR-10028: "Cryo-EM structure of a Plasmodium falciparum 80S ribosome bound to the anti-protozoan drug emetine" from Wong et al. (2014)</li> <li>EMPIAR-10049: "Molecular Mechanism of V(D)J Recombination from Synaptic RAG1-RAG2 Complex Structures" from Ru et al. (2015)</li> <li>EMPIAR-10076: "Modular assembly of the large bacterial ribosome" from Davis et al. (2016)</li> <li>EMPIAR-10180: "Structure of a pre-catalytic spliceosome" from Plaschka et al. (2017)</li> </ul> Synthetic datasets with simulated heterogeneity and their ground truth density maps, poses, and labels: <ul> <li>Uniform: 50k particle images (128x128, 6A/pix) uniformly sampled from 50 models along a 1-dimensional reaction coordinate</li> <li>Cooperative: 50k particle images (128x128, 6A/pix) sampled along the above reaction coordinate according to a 3-component Gaussian mixture model with overlapping components </li> <li>Noncontiguous: 50k particle images (128x128, 6A/pix) sampled along the above reaction coordinate according to a 3-component Gaussian mixture model without overlapping components</li> <li>Ribosomes: 50k particle images (128x128, 3A/pix) containing a mixture of 30S, 50S, 70S ribosomes simulating compositional heterogeneity</li> </ul>

opencc-zeroJul 2021View details →

Data from: How to make methodological decisions when inferring social networks.

Social network analyses allow studying the processes underlying the associations between individuals and the consequences of those associations. Constructing and analysing social networks can be challenging, especially when designing new studies as researchers are confronted with decisions about how to collect data and construct networks, and the answers are not always straightforward. The current lack of guidance on building a social network for a new study system might lead researchers to try several different methods, and risk generating false results arising from multiple hypotheses testing. Here, we suggest an approach for making decisions when starting social network research in a new study system that avoids the pitfall of multiple hypotheses testing. We argue that best edge definition for a network is a decision that can be made using a priori knowledge about the species, and that is independent from the hypotheses that the network will ultimately be used to evaluate. We illustrate this approach with a study conducted on a colonial cooperatively breeding bird, the sociable weaver. We first identified two ways of collecting data using different numbers of feeders and three ways to define associations among birds. We then evaluated which combination of data collection and association definition maximised (i) the assortment of individuals into previously known 'breeding groups' (birds that contribute towards the same nest and maintain cohesion when foraging), and (ii) socially differentiated relationships (more strong and weak relationships than expected by chance). This evaluation of different methods based on a priori knowledge of the study species can be implemented in a diverse array of study systems and makes the case for using existing, biologically meaningful knowledge about a system to help navigate the myriad of methodological decisions about data collection and network inference.

opencc-zeroJan 2021View details →

Interaction network for eleven Cucurbita pepo sites in Guatemala

In recent years, evidence has been found that plant-pollinator interactions are altered by land-use and that genetic diversity also plays a role. However, how land-use and genetic diversity influence plant-pollinator interactions, particularly in the Neotropics, where many endemic plants exist is still an open question. Cucurbita pepo is a monoecious plant and traditional crop wide distributed, with high rates of molecular evolution, landraces associated with human cultural management and a history of coevolution with bees, which makes this species a promising model for studying the effect of landscape and genetic diversity on plant-pollinator interactions. Here, we assess 1) whether female and male flowers differences have an effect on the interaction network, 2) how C. pepo genetic diversity affects flower-bee visitation network structure, and 3) what is the effect that land-use, accounting for C. pepo genetic variability, has on pumpkin-bee interaction network variables. Our results indicate that female and male flowers presented the same community composition and network structure suggesting that the differences do not have a significant effect on network evolution. Genetic diversity has a positive effect on modularity, nestedness, and number of interactions, which, when considered, allows to observe how land-use variables can have an enhancing or buffering effect on nestedness. Our results suggest that considering genetic diversity is relevant for a better understanding of the effect of landscape on interaction networks. Additionally, this understanding has great value in conserving biodiversity and enhancing the stability of interaction networks in a world facing great challenges of habitat and diversity loss.

Data and Code for Inequality is rising where social network segregation interacts with urban topology

This folder contains data and code to reproduce results of the paper "Inequality is rising where social network segregation interacts with urban topology". arXiv version: https://arxiv.org/abs/1909.11414.

opennotspecifiedJan 2021View details →

FIGURE 4. Combined haplotype networks from CytB data for Laminatubus paulbrooksi n in Laminatubus (Serpulidae, Annelida) from eastern Pacific hydrothermal vents and methane seeps, with description of two new species

FIGURE 4. Combined haplotype networks from CytB data for Laminatubus paulbrooksi n. sp. (top) from Pacific Costa Rica margin and Gulf of California (Mexico) localities and L. joycebrooksae n. sp. (bottom) from Costa Rica. There was little variability among the L. joycebrooksae n. sp. sequences and a distinct break to L. paulbrooksi n. sp. This corresponds to a minimum 6.4% uncorrected distance. Laminatubus paulbrooksi n. sp. showed marked intraspecific variability with distinct breaks among the three main sites; Costa Rica (9°N), Pescadero (23°N) and Guaymas Basin (27°N). * indicates the holotypes for L. paulbrooksi n. sp. and L. joycebrooksae n. sp. respectively.

Supplementary Material: Exposing Previously Undetectable Faults in Deep Neural Networks

Supplementary material for ISSTA 2021 submission #58. The supplementary material is under 600MB and uploaded before the submission deadline, but uploading to the submission website did not work. Editing this supplementary material is not possible after upload.

Structural brain network abnormalities and the probability of seizure recurrence after epilepsy surgery

Supplementary code and data for "Structural brain network abnormalities and the probability of seizure recurrence after epilepsy surgery"  https://doi.org/10.1212/WNL.0000000000011315

opencc-by-4.0Nov 2020View details →

Printability, durability, contractility and vascular network formation in 3D bioprinted cardiac endothelial cells using alginate-gelatin hydrogels

TBC

opencc-zeroDec 2016View details →

Data from: Finding the best management policy to eradicate invasive species from spatial ecological networks with simultaneous actions

1. Spatial management of invasive species is more likely to be successful when multiple locations are treated simultaneously. However, selecting the best locations to act is difficult due to the many options available at any time. 2. We design a near-optimal policy for applying multiple actions simultaneously for faster invasive species control within a network. Our method uses a recent optimisation tool, the Graph-based Markov decision process (GMDP). Since the policy can be difficult to interpret, we extracted a simpler policy using classification trees. We applied our approach to the eradication of invasive mosquitofish (Gambusia holbrooki) from the habitat of the red-finned blue-eye (Scaturiginichthys vermeilipinnis), a critically endangered fish with a global population that is restricted to seven artesian springs in Queensland, Australia. 3. The policy returned by the GMDP was to manage springs occupied by mosquitofish and their connected neighbours, unless the neighbours were occupied by red-finned blue-eyes. 4. Simultaneous management resulted in rapid declines in simulated mosquitofish occupancy even if eradication effectiveness was low; however the cost of simultaneous eradication was high and sustained eradication effort was necessary to maintain low mosquitofish occupancy. 5. Synthesis and applications. Our paper finds a near-optimal, multi-action control policy to remove an invasive species from a multi-species spatial network. We introduce the Graph-based Markov decision process (GMDP) and apply it to a real case study – eradication of invasive mosquitofish from the habitat of the red-finned blue-eye. We find that the GMDP can generate policies for networks with extremely large state spaces, however it works best when nodes have fewer than five neighbours. We conclude that simultaneous eradications are effective for rapid control of invasive species; however, managers should consider the cost and time required for an effective eradication program.

opencc-zeroDec 2016View details →

Data from: Fire influences the structure of plant-bee networks

1. Fire represents a frequent disturbance in many ecosystems, which can affect plant-pollinator assemblages and hence the services they provide. Furthermore, fire events could affect the architecture of plant-pollinator interaction networks, modifying the structure and function of communities. 2. Some pollinators, such as wood-nesting bees, may be particularly affected by fire events due to damage to nesting material and its long regeneration time. However, it remains unclear whether fire influences the structure of bee plant interactions. 3. Here, we used quantitative plant-wood nesting bee interaction networks sampled across four different post-fire age categories (from freshly-burnt to unburnt sites) in an arid ecosystem to test whether the abundance of wood-nesting bees, the breadth of resource use and the plant-bee community structure change along a post-fire age gradient. 4. We demonstrate that freshly-burnt sites present higher abundances of generalist than specialist wood-nesting bees and this translates into lower network modularity than that of sites with greater post-fire ages. Bees do not seem to change their feeding behaviour across the post-fire age gradient despite changes in floral resource availability. 5. Despite the effects of fire on plant-bee interaction network structure, these mutualistic networks seem to be able to recover a few years after the fire event. This result suggests that these interactions might be highly resilient to this type of disturbance.