TY - JOUR
AB - A cornerstone of statistical inference, the maximum entropy framework is being increasingly applied to construct descriptive and predictive models of biological systems, especially complex biological networks, from large experimental data sets. Both its broad applicability and the success it obtained in different contexts hinge upon its conceptual simplicity and mathematical soundness. Here we try to concisely review the basic elements of the maximum entropy principle, starting from the notion of ‘entropy’, and describe its usefulness for the analysis of biological systems. As examples, we focus specifically on the problem of reconstructing gene interaction networks from expression data and on recent work attempting to expand our system-level understanding of bacterial metabolism. Finally, we highlight some extensions and potential limitations of the maximum entropy approach, and point to more recent developments that are likely to play a key role in the upcoming challenges of extracting structures and information from increasingly rich, high-throughput biological data.
AU - De Martino, Andrea
AU - De Martino, Daniele
ID - 306
IS - 4
JF - Heliyon
TI - An introduction to the maximum entropy approach and its application to inference problems in biology
VL - 4
ER -
TY - JOUR
AB - Spontaneous emission spectra of two initially excited closely spaced identical atoms are very sensitive to the strength and the direction of the applied magnetic field. We consider the relevant schemes that ensure the determination of the mutual spatial orientation of the atoms and the distance between them by entirely optical means. A corresponding theoretical description is given accounting for the dipole-dipole interaction between the two atoms in the presence of a magnetic field and for polarizations of the quantum field interacting with magnetic sublevels of the two-atom system.
AU - Redchenko, Elena
AU - Makarov, Alexander
AU - Yudson, Vladimir
ID - 307
IS - 4
JF - Physical Review A - Atomic, Molecular, and Optical Physics
TI - Nanoscopy of pairs of atoms by fluorescence in a magnetic field
VL - 97
ER -
TY - JOUR
AB - Migrating cells penetrate tissue barriers during development, inflammatory responses, and tumor metastasis. We study if migration in vivo in such three-dimensionally confined environments requires changes in the mechanical properties of the surrounding cells using embryonic Drosophila melanogaster hemocytes, also called macrophages, as a model. We find that macrophage invasion into the germband through transient separation of the apposing ectoderm and mesoderm requires cell deformations and reductions in apical tension in the ectoderm. Interestingly, the genetic pathway governing these mechanical shifts acts downstream of the only known tumor necrosis factor superfamily member in Drosophila, Eiger, and its receptor, Grindelwald. Eiger-Grindelwald signaling reduces levels of active Myosin in the germband ectodermal cortex through the localization of a Crumbs complex component, Patj (Pals-1-associated tight junction protein). We therefore elucidate a distinct molecular pathway that controls tissue tension and demonstrate the importance of such regulation for invasive migration in vivo.
AU - Ratheesh, Aparna
AU - Biebl, Julia
AU - Smutny, Michael
AU - Veselá, Jana
AU - Papusheva, Ekaterina
AU - Krens, Gabriel
AU - Kaufmann, Walter
AU - György, Attila
AU - Casano, Alessandra M
AU - Siekhaus, Daria E
ID - 308
IS - 3
JF - Developmental Cell
TI - Drosophila TNF modulates tissue tension in the embryo to facilitate macrophage invasive migration
VL - 45
ER -
TY - CONF
AB - We present an efficient algorithm for a problem in the interface between clustering and graph embeddings. An embedding ' : G ! M of a graph G into a 2manifold M maps the vertices in V (G) to distinct points and the edges in E(G) to interior-disjoint Jordan arcs between the corresponding vertices. In applications in clustering, cartography, and visualization, nearby vertices and edges are often bundled to a common node or arc, due to data compression or low resolution. This raises the computational problem of deciding whether a given map ' : G ! M comes from an embedding. A map ' : G ! M is a weak embedding if it can be perturbed into an embedding ψ: G ! M with k' "k < " for every " > 0. A polynomial-time algorithm for recognizing weak embeddings was recently found by Fulek and Kyncl [14], which reduces to solving a system of linear equations over Z2. It runs in O(n2!) O(n4:75) time, where 2:373 is the matrix multiplication exponent and n is the number of vertices and edges of G. We improve the running time to O(n log n). Our algorithm is also conceptually simpler than [14]: We perform a sequence of local operations that gradually "untangles" the image '(G) into an embedding (G), or reports that ' is not a weak embedding. It generalizes a recent technique developed for the case that G is a cycle and the embedding is a simple polygon [1], and combines local constraints on the orientation of subgraphs directly, thereby eliminating the need for solving large systems of linear equations.
AU - Akitaya, Hugo
AU - Fulek, Radoslav
AU - Tóth, Csaba
ID - 309
TI - Recognizing weak embeddings of graphs
ER -
TY - JOUR
AB - Correlations in sensory neural networks have both extrinsic and intrinsic origins. Extrinsic or stimulus correlations arise from shared inputs to the network and, thus, depend strongly on the stimulus ensemble. Intrinsic or noise correlations reflect biophysical mechanisms of interactions between neurons, which are expected to be robust to changes in the stimulus ensemble. Despite the importance of this distinction for understanding how sensory networks encode information collectively, no method exists to reliably separate intrinsic interactions from extrinsic correlations in neural activity data, limiting our ability to build predictive models of the network response. In this paper we introduce a general strategy to infer population models of interacting neurons that collectively encode stimulus information. The key to disentangling intrinsic from extrinsic correlations is to infer the couplings between neurons separately from the encoding model and to combine the two using corrections calculated in a mean-field approximation. We demonstrate the effectiveness of this approach in retinal recordings. The same coupling network is inferred from responses to radically different stimulus ensembles, showing that these couplings indeed reflect stimulus-independent interactions between neurons. The inferred model predicts accurately the collective response of retinal ganglion cell populations as a function of the stimulus.
AU - Ferrari, Ulisse
AU - Deny, Stephane
AU - Chalk, Matthew J
AU - Tkacik, Gasper
AU - Marre, Olivier
AU - Mora, Thierry
ID - 31
IS - 4
JF - Physical Review E
SN - 24700045
TI - Separating intrinsic interactions from extrinsic correlations in a network of sensory neurons
VL - 98
ER -
TY - CONF
AB - A model of computation that is widely used in the formal analysis of reactive systems is symbolic algorithms. In this model the access to the input graph is restricted to consist of symbolic operations, which are expensive in comparison to the standard RAM operations. We give lower bounds on the number of symbolic operations for basic graph problems such as the computation of the strongly connected components and of the approximate diameter as well as for fundamental problems in model checking such as safety, liveness, and coliveness. Our lower bounds are linear in the number of vertices of the graph, even for constant-diameter graphs. For none of these problems lower bounds on the number of symbolic operations were known before. The lower bounds show an interesting separation of these problems from the reachability problem, which can be solved with O(D) symbolic operations, where D is the diameter of the graph. Additionally we present an approximation algorithm for the graph diameter which requires Õ(n/D) symbolic steps to achieve a (1 +ϵ)-approximation for any constant > 0. This compares to O(n/D) symbolic steps for the (naive) exact algorithm and O(D) symbolic steps for a 2-approximation. Finally we also give a refined analysis of the strongly connected components algorithms of [15], showing that it uses an optimal number of symbolic steps that is proportional to the sum of the diameters of the strongly connected components.
AU - Chatterjee, Krishnendu
AU - Dvorák, Wolfgang
AU - Henzinger, Monika
AU - Loitzenbauer, Veronika
ID - 310
TI - Lower bounds for symbolic computation on graphs: Strongly connected components, liveness, safety and diameter
ER -
TY - JOUR
AB - Motivated by biological questions, we study configurations of equal spheres that neither pack nor cover. Placing their centers on a lattice, we define the soft density of the configuration by penalizing multiple overlaps. Considering the 1-parameter family of diagonally distorted 3-dimensional integer lattices, we show that the soft density is maximized at the FCC lattice.
AU - Edelsbrunner, Herbert
AU - Iglesias Ham, Mabel
ID - 312
IS - 1
JF - SIAM J Discrete Math
SN - 08954801
TI - On the optimality of the FCC lattice for soft sphere packing
VL - 32
ER -
TY - JOUR
AB - The interface of physics and biology pro-vides a fruitful environment for generatingnew concepts and exciting ways forwardto understanding living matter. Examplesof successful studies include the estab-lishment and readout of morphogen gra-dients during development, signal pro-cessing in protein and genetic networks,the role of ﬂuctuations in determining thefates of cells and tissues, and collectiveeffects in proteins and in tissues. It is nothard to envision that signiﬁcant further ad-vances will translate to societal beneﬁtsby initiating the development of new de-vices and strategies for curing disease.However, research at the interface posesvarious challenges, in particular for youngscientists, and current institutions arerarely designed to facilitate such scientiﬁcprograms. In this Letter, we propose aninternational initiative that addressesthese challenges through the establish-ment of a worldwide network of platformsfor cross-disciplinary training and incuba-tors for starting new collaborations.
AU - Bauer, Guntram
AU - Fakhri, Nikta
AU - Kicheva, Anna
AU - Kondev, Jané
AU - Kruse, Karsten
AU - Noji, Hiroyuki
AU - Riveline, Daniel
AU - Saunders, Timothy
AU - Thatta, Mukund
AU - Wieschaus, Eric
ID - 314
IS - 4
JF - Cell Systems
TI - The science of living matter for tomorrow
VL - 6
ER -
TY - JOUR
AB - We replace the established aluminium gates for the formation of quantum dots in silicon with gates made from palladium. We study the morphology of both aluminium and palladium gates with transmission electron microscopy. The native aluminium oxide is found to be formed all around the aluminium gates, which could lead to the formation of unintentional dots. Therefore, we report on a novel fabrication route that replaces aluminium and its native oxide by palladium with atomic-layer-deposition-grown aluminium oxide. Using this approach, we show the formation of low-disorder gate-defined quantum dots, which are reproducibly fabricated. Furthermore, palladium enables us to further shrink the gate design, allowing us to perform electron transport measurements in the few-electron regime in devices comprising only two gate layers, a major technological advancement. It remains to be seen, whether the introduction of palladium gates can improve the excellent results on electron and nuclear spin qubits defined with an aluminium gate stack.
AU - Brauns, Matthias
AU - Amitonov, Sergey
AU - Spruijtenburg, Paul
AU - Zwanenburg, Floris
ID - 317
IS - 1
JF - Scientific Reports
TI - Palladium gates for reproducible quantum dots in silicon
VL - 8
ER -
TY - JOUR
AB - The insect’s fat body combines metabolic and immunological functions. In this issue of Developmental Cell, Franz et al. (2018) show that in Drosophila, cells of the fat body are not static, but can actively “swim” toward sites of epithelial injury, where they physically clog the wound and locally secrete antimicrobial peptides.
AU - Casano, Alessandra M
AU - Sixt, Michael K
ID - 318
IS - 4
JF - Developmental Cell
TI - A fat lot of good for wound healing
VL - 44
ER -