scholarly journals Quantitative understanding of molecular competition as a hidden layer of gene regulatory network

2018 ◽  
Author(s):  
Ye Yuan ◽  
Lei Wei ◽  
Tao Hu ◽  
Shuailin Li ◽  
Tianrun Cheng ◽  
...  
Keyword(s):  
Biological Networks ◽  
Regulatory Mechanism ◽  
Response Speed ◽  
Coarse Grained ◽  
Motif Model ◽  
Molecular Systems ◽  
Trade Offs ◽  
Quantitative Understanding ◽  
Hidden Layer ◽  
Cellular Components

AbstractMolecular competition is ubiquitous, essential and multifunctional throughout diverse biological processes. Competition brings about trade-offs of shared limited resources among the cellular components, and it thus introduce a hidden layer of regulatory mechanism by connecting components even without direct physical interactions. By abstracting the analogous competition mechanism behind diverse molecular systems, we built a unified coarse-grained competition motif model to systematically compare experimental evidences in these processes and analyzed general properties shared behind them. We could predict in what molecular environments competition would reveal threshold behavior or display a negative linear dependence. We quantified how competition can shape regulator-target dose-response curve, modulate dynamic response speed, control target expression noise, and introduce correlated fluctuations between targets. This work uncovered the complexity and generality of molecular competition effect, which might act as a hidden regulatory mechanism with multiple functions throughout biological networks in both natural and synthetic systems.

You Only Traverse Twice: A YOTT Placement, Routing, and Timing Approach for CGRAs

2021 ◽  
Vol 20 (5s) ◽  
pp. 1-25
Author(s):  
Michael Canesche ◽  
Westerley Carvalho ◽  
Lucas Reis ◽  
Matheus Oliveira ◽  
Salles Magalhães ◽  
...  
Keyword(s):  
Execution Time ◽  
High Performance ◽  
Coarse Grained ◽  
Optimal Placement ◽  
Greedy Heuristics ◽  
High Quality ◽  
Solution Quality ◽  
Graph Traversal ◽  
Trade Offs ◽  
Graph Properties

Coarse-grained reconfigurable architecture (CGRA) mapping involves three main steps: placement, routing, and timing. The mapping is an NP-complete problem, and a common strategy is to decouple this process into its independent steps. This work focuses on the placement step, and its aim is to propose a technique that is both reasonably fast and leads to high-performance solutions. Furthermore, a near-optimal placement simplifies the following routing and timing steps. Exact solutions cannot find placements in a reasonable execution time as input designs increase in size. Heuristic solutions include meta-heuristics, such as Simulated Annealing (SA) and fast and straightforward greedy heuristics based on graph traversal. However, as these approaches are probabilistic and have a large design space, it is not easy to provide both run-time efficiency and good solution quality. We propose a graph traversal heuristic that provides the best of both: high-quality placements similar to SA and the execution time of graph traversal approaches. Our placement introduces novel ideas based on “you only traverse twice” (YOTT) approach that performs a two-step graph traversal. The first traversal generates annotated data to guide the second step, which greedily performs the placement, node per node, aided by the annotated data and target architecture constraints. We introduce three new concepts to implement this technique: I/O and reconvergence annotation, degree matching, and look-ahead placement. Our analysis of this approach explores the placement execution time/quality trade-offs. We point out insights on how to analyze graph properties during dataflow mapping. Our results show that YOTT is 60.6 , 9.7 , and 2.3 faster than a high-quality SA, bounding box SA VPR, and multi-single traversal placements, respectively. Furthermore, YOTT reduces the average wire length and the maximal FIFO size (additional timing requirement on CGRAs) to avoid delay mismatches in fully pipelined architectures.

Playing With BEARS: Balancing Effort, Accuracy, and Response Speed in a Semantic Feature Verification Anomia Treatment Game

2021 ◽  
pp. 1-27
Author(s):  
William S. Evans ◽  
Robert Cavanaugh ◽  
Yina Quique ◽  
Emily Boss ◽  
Jeffrey J. Starns ◽  
...  
Keyword(s):  
Treatment Outcomes ◽  
Retrieval Practice ◽  
Single Case ◽  
Case Series ◽  
Response Speed ◽  
Semantic Feature ◽  
System Calibration ◽  
Trade Offs ◽  
Practice Efficiency ◽  
Speed Accuracy

Purpose The purpose of this study was to develop and pilot a novel treatment framework called BEARS (Balancing Effort, Accuracy, and Response Speed). People with aphasia (PWA) have been shown to maladaptively balance speed and accuracy during language tasks. BEARS is designed to train PWA to balance speed–accuracy trade-offs and improve system calibration (i.e., to adaptively match system use with its current capability), which was hypothesized to improve treatment outcomes by maximizing retrieval practice and minimizing error learning. In this study, BEARS was applied in the context of a semantically oriented anomia treatment based on semantic feature verification (SFV). Method Nine PWA received 25 hr of treatment in a multiple-baseline single-case series design. BEARS + SFV combined computer-based SFV with clinician-provided BEARS metacognitive training. Naming probe accuracy, efficiency, and proportion of “pass” responses on inaccurate trials were analyzed using Bayesian generalized linear mixed-effects models. Generalization to discourse and correlations between practice efficiency and treatment outcomes were also assessed. Results Participants improved on naming probe accuracy and efficiency of treated and untreated items, although untreated item gains could not be distinguished from the effects of repeated exposure. There were no improvements on discourse performance, but participants demonstrated improved system calibration based on their performance on inaccurate treatment trials, with an increasing proportion of “pass” responses compared to paraphasia or timeout nonresponses. In addition, levels of practice efficiency during treatment were positively correlated with treatment outcomes, suggesting that improved practice efficiency promoted greater treatment generalization and improved naming efficiency. Conclusions BEARS is a promising, theoretically motivated treatment framework for addressing the interplay between effort, accuracy, and processing speed in aphasia. This study establishes the feasibility of BEARS + SFV and provides preliminary evidence for its efficacy. This study highlights the importance of considering processing efficiency in anomia treatment, in addition to performance accuracy. Supplemental Material https://doi.org/10.23641/asha.14935812

scholarly journals CellNetVis: a web tool for visualization of biological networks using force-directed layout constrained by cellular components

2017 ◽  
Author(s):  
Henry Heberle ◽  
Marcelo Falsarella Carazzolle ◽  
Guilherme P. Telles ◽  
Gabriela Vaz Meirelles ◽  
Rosane Minghim
Keyword(s):  
Biological Networks ◽  
Visual Exploration ◽  
Web Tool ◽  
Biomolecular Interaction ◽  
Dense Networks ◽  
A Cell ◽  
Visualization Of Data ◽  
Cellular Compartments ◽  
Cellular Components ◽  
Dynamic Investigation

AbstractBackgroundThe advent of “omics” science has brought new perspectives in contemporary biology through the high-throughput analyses of molecular interactions, providing new clues in protein/gene function and in the organization of biological pathways. Biomolecular interaction networks, or graphs, are simple abstract representations where the components of a cell (e.g. proteins, metabolites etc.) are represented by nodes and their interactions are represented by edges. An appropriate visualization of data is crucial for understanding such networks, since pathways are related to functions that occur in specific regions of the cell. The force-directed layout is an important and widely used technique to draw networks according to their topologies. Placing the networks into cellular compartments helps to quickly identify where network elements are located and, more specifically, concentrated. Currently, only a few tools provide the capability of visually organizing networks by cellular compartments. Most of them cannot handle large and dense networks. Even for small networks with hundreds of nodes the available tools are not able to reposition the network while the user is interacting, limiting the visual exploration capability.ResultsHere we propose CellNetVis, a web tool to easily display biological networks in a cell diagram employing a constrained force-directed layout algorithm. The tool is freely available and open-source. It was originally designed for networks generated by the Integrated Interactome System and can be used with networks from others databases, like InnateDB.ConclusionsCellNetVis has demonstrated to be applicable for dynamic investigation of complex networks over a consistent representation of a cell on the Web, with capabilities not matched elsewhere.

scholarly journals Swarm-CG: Automatic Parametrization of Bonded Terms in Coarse-Grained Models of Simple to Complex Molecules via Fuzzy Self-Tuning Particle Swarm Optimization

2020 ◽  
Author(s):  
Charly Empereur-mot ◽  
Luca Pesce ◽  
Davide Bochicchio ◽  
Claudio Perego ◽  
Giovanni M. Pavan
Keyword(s):  
Particle Swarm Optimization ◽  
State Of The Art ◽  
Structural Complexity ◽  
Coarse Grained ◽  
Complex Molecules ◽  
Swarm Optimization ◽  
Molecular Systems ◽  
Self Tuning ◽  
User Friendly ◽  
Python Package

We present Swarm-CG, a versatile software for the automatic parametrization of bonded parameters in coarse-grained (CG) models. By coupling state-of-the-art metaheuristics to Boltzmann inversion, Swarm-CG performs accurate parametrization of bonded terms in CG models composed of up to 200 pseudoatoms within 4h-24h on standard desktop machines, using an AA trajectory as reference and default<br>settings of the software. The software benefits from a user-friendly interface and two different usage modes (default and advanced). We particularly expect Swarm-CG to support and facilitate the development of new CG models for the study of molecular systems interesting for bio- and nanotechnology.<br>Excellent performances are demonstrated using a benchmark of 9 molecules of diverse nature, structural complexity and size. Swarm-CG usage is ideal in combination with popular CG force<br>fields, such as e.g. MARTINI. However, we anticipate that in principle its versatility makes it well suited for the optimization of models built based also on other CG schemes. Swarm-CG is available with all its dependencies via the Python Package Index (PIP package: swarm-cg). Tutorials and demonstration data are available at: www.github.com/GMPavanLab/SwarmCG.

scholarly journals Coarse-grained tight-binding models

2021 ◽  
Author(s):  
Tianxiang Liu ◽  
Li Mao ◽  
Mats-Erik Pistol ◽  
Craig Pryor
Keyword(s):  
Quantum Well ◽  
Computing Time ◽  
Numerical Test ◽  
Tight Binding ◽  
Computation Time ◽  
Coarse Grained ◽  
Weakly Bound ◽  
Trade Offs ◽  
Full Calculation ◽  
Binding Models

Abstract Calculating the electronic structure of systems involving very different length scales presents a challenge. Empirical atomistic descriptions such as pseudopotentials or tight-binding models allow one to calculate the effects of atomic placements, but the computational burden increases rapidly with the size of the system, limiting the ability to treat weakly bound extended electronic states. Here we propose a new method to connect atomistic and quasi-continuous models, thus speeding up tight-binding calculations for large systems. We divide a structure into blocks consisting of several unit cells which we diagonalize individually. We then construct a tight-binding Hamiltonian for the full structure using a truncated basis for the blocks, ignoring states having large energy eigenvalues and retaining states with an energy close to the band edge energies. A numerical test using a GaAs/AlAs quantum well shows the computation time can be decreased to less than 5% of the full calculation with errors of less than 1%. We give data for the trade-offs between computing time and loss of accuracy. We also tested calculations of the density of states for a GaAs/AlAs quantum well and find a ten times speedup without much loss in accuracy.

scholarly journals Self Assembly of Model Polymers into Biological Random Networks

2020 ◽  
Author(s):  
Matthew Bailey ◽  
Mark Wilson
Keyword(s):  
Network Structure ◽  
Biological Networks ◽  
Self Assembly ◽  
Short Range ◽  
External Pressure ◽  
Coarse Grained ◽  
Random Networks ◽  
Network Structures ◽  
Polymer Model ◽  
Microscope Images

<div>The properties of biological networks, such as those found in the ocular lens capsule, are difficult to study without simplified models.</div><div>Model polymers are developed, inspired by "worm-like'' curve models, that are shown to spontaneously self assemble</div><div>to form networks similar to those observed experimentally in biological systems.</div><div>These highly simplified coarse-grained models allow the self assembly process to be studied on near-realistic time-scales.</div><div>Metrics are developed (using a polygon-based framework)</div><div>which are useful for describing simulated networks and can also be applied to images of real networks.</div><div>These metrics are used to show the range of control that the computational polymer model has over the networks, including the polygon structure and short range order.</div><div>The structure of the simulated networks are compared to previous simulation work and microscope images of real networks. </div><div>The network structure is shown to be a function of the interaction strengths, cooling rates and external pressure. </div><div>In addition, "pre-tangled'' network structures are introduced and shown to significantly influence the subsequent network structure.</div><div>The network structures obtained fit into a region of the network landscape effectively inaccessible to random</div><div>(entropically-driven) networks but which are occupied by experimentally-derived configurations.</div>

An efficient coarse-grained approach for the electron transport through large molecular systems under dephasing environment

2016 ◽  
Vol 89 (4) ◽  
Author(s):  
Daijiro Nozaki ◽  
Raul Bustos-Marún ◽  
Carlos J. Cattena ◽  
Gianaurelio Cuniberti ◽  
Horacio M. Pastawski
Keyword(s):  
Electron Transport ◽  
Coarse Grained ◽  
Molecular Systems

Compatible observable decompositions for coarse-grained representations of real molecular systems

2019 ◽  
Vol 151 (13) ◽  
pp. 134115 ◽  
Author(s):  
Thomas Dannenhoffer-Lafage ◽  
Jacob W. Wagner ◽  
Aleksander E. P. Durumeric ◽  
Gregory A. Voth
Keyword(s):  
Coarse Grained ◽  
Molecular Systems

Parametrizing coarse grained models for molecular systems at equilibrium

2016 ◽  
Vol 225 (8-9) ◽  
pp. 1347-1372 ◽  
Author(s):  
E. Kalligiannaki ◽  
A. Chazirakis ◽  
A. Tsourtis ◽  
M.A. Katsoulakis ◽  
P. Plecháč ◽  
...  
Keyword(s):  
Coarse Grained ◽  
Molecular Systems

scholarly journals CellNetVis: a web tool for visualization of biological networks using force-directed layout constrained by cellular components

2017 ◽  
Vol 18 (S10) ◽  
Author(s):  
Henry Heberle ◽  
Marcelo Falsarella Carazzolle ◽  
Guilherme P. Telles ◽  
Gabriela Vaz Meirelles ◽  
Rosane Minghim
Keyword(s):  
Biological Networks ◽  
Web Tool ◽  
Cellular Components
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