Robustness of Network Measures to Link Errors

In various applications involving complex networks, network measures are employed to assess the relative importance of network nodes. However, the robustness of such measures in the presence of link inaccuracies has not been well characterized. Here we present two simple stochastic models of false and missing links and study the effect of link errors on three commonly used node centrality measures: degree centrality, betweenness centrality, and dynamical importance. We perform numerical simulations to assess robustness of these three centrality measures. We also develop an analytical theory, which we compare with our simulations, obtaining very good agreement.Comment: 9 pages, 9 figure

Making Predictions and Handling Errors in Reconstructed Biological Networks

In this thesis we present methods for applying techniques from complex network theory to analyze and interpret inferred biological interactions. With the advent of high throughput technologies such as gene microarrays and genome-wide sequencing, it is now possible to measure the activity of every gene in a cancer cell population under different conditions. How to extract important interactions from these experiments remains an outstanding question. Here we present a method to identify these key interactions by focusing on short paths in a transcription factor network. We use a mutual information-based approach to infer the transcription factor network from gene expression microarrays, which measure perturbations in a Diffuse Large B Cell Lymphoma cell line. By focusing on the number of short paths between transcription factors and signature genes in the inferred network, we find a set of transcription factors whose biology is crucial to the continued survival of these lymphoma cells and also show that a subset of these factors have a distinct expression pattern in patient tumors as well. As many networks of interest are reconstructed from data containing errors, we introduce two simple models of false and missing links to characterize the effects of network misinformation on three commonly used centrality measures: degree centrality, betweenness centrality, and dynamical importance. We show that all three measures are especially robust to both false and missing links when the network has a power law in the tail of its degree distribution

External Periodic Driving of Large Systems of Globally Coupled Phase Oscillators

Large systems of coupled oscillators subjected to a periodic external drive occur in many situations in physics and biology. Here the simple, paradigmatic case of equal-strength, all-to-all sine-coupling of phase oscillators subject to a sinusoidal external drive is considered. The stationary states and their stability are determined. Using the stability information and numerical experiments, parameter space phase diagrams showing when different types of system behavior apply are constructed, and the bifurcations marking transitions between different types of behavior are delineated. The analysis is supported by results of direct numerical simulation of an ensemble of oscillators

Identification of an emphysema- associated genetic variant near TGFB2 with regulatory effects in lung fibroblasts

Murine studies have linked TGF-β signaling to emphysema, and human genome-wide association studies (GWAS) studies of lung function and COPD have identified associated regions near genes in the TGF-β superfamily. However, the functional regulatory mechanisms at these loci have not been identified. We performed the largest GWAS of emphysema patterns to date, identifying 10 GWAS loci including an association peak spanning a 200 kb region downstream from TGFB2. Integrative analysis of publicly available eQTL, DNaseI, and chromatin conformation data identified a putative functional variant, rs1690789, that may regulate TGFB2 expression in human fibroblasts. Using chromatin conformation capture, we confirmed that the region containing rs1690789 contacts the TGFB2 promoter in fibroblasts, and CRISPR/Cas-9 targeted deletion of a ~ 100 bp region containing rs1690789 resulted in decreased TGFB2 expression in primary human lung fibroblasts. These data provide novel mechanistic evidence linking genetic variation affecting the TGF-β pathway to emphysema in humans

Ergänzungen zur iberischen Pseudoscorpioniden-Fauna

Die systematischen Aufsammlungen, die Prof. Dr. H. Franz in den letzten Jahren in weiten Teilen der iberischen Halbinsel durchführte, schliessen weitgehend die Lücken, die bisher noch zwischen den explorierten Gebieten klafften. Sie ergänzen und berichtigen daher unsere bisherigen, von mir letztmals 1955 (Eos, XXXI, pp. 87-122) zusammengefassten Kenntnisse in taxonomischer und faunistischer Hinsicht und runden das Faunenbild auch tiergeographisch zu erfreulicher Vollständigkeit ab. Die Ausbeuten enthielten wiederum 8 neue Arten beziehungsweise Unterarten. Drei weitere Arten waren für Spanien neu. In den cantabrischen Gebirgen tritt nunmehr die Gattung Microcreagris als charakteristisches Faunenelement noch stärker hervor.— Im folgenden werden die seither gemachten Funde angeführt.Peer reviewe

Transcription-driven genome organization::A model for chromosome structure and the regulation of gene expression tested through simulations

Current models for the folding of the human genome see a hierarchy stretching down from chromosome territories, through A/B compartments and topologically-associating domains (TADs), to contact domains stabilized by cohesin and CTCF. However, molecular mechanisms underlying this folding, and the way folding affects transcriptional activity, remain obscure. Here we review physical principles driving proteins bound to long polymers into clusters surrounded by loops, and present a parsimonious yet comprehensive model for the way the organization determines function. We argue that clusters of active RNA polymerases and their transcription factors are major architectural features; then, contact domains, TADs and compartments just reflect one or more loops and clusters. We suggest tethering a gene close to a cluster containing appropriate factors—a transcription factory—increases the firing frequency, and offer solutions to many current puzzles concerning the actions of enhancers, super-enhancers, boundaries and eQTLs (expression quantitative trait loci). As a result, the activity of any gene is directly influenced by the activity of other transcription units around it in 3D space, and this is supported by Brownian-dynamics simulations of transcription factors binding to cognate sites on long polymers

The Network Zoo: a multilingual package for the inference and analysis of gene regulatory networks

Inference and analysis of gene regulatory networks (GRNs) require software that integrates multi-omic data from various sources. The Network Zoo (netZoo; netzoo.github.io) is a collection of open-source methods to infer GRNs, conduct differential network analyses, estimate community structure, and explore the transitions between biological states. The netZoo builds on our ongoing development of network methods, harmonizing the implementations in various computing languages and between methods to allow better integration of these tools into analytical pipelines. We demonstrate the utility using multi-omic data from the Cancer Cell Line Encyclopedia. We will continue to expand the netZoo to incorporate additional methods