scholarly journals Joint epitope selection and spacer design for string-of-beads vaccines

2020 ◽  
Author(s):  
Emilio Dorigatti ◽  
Benjamin Schubert
Keyword(s):  
Antigen Processing ◽  
State Of The Art ◽  
Computational Approach ◽  
Population Coverage ◽  
Current State ◽  
Fixed Set ◽  
Epitope Selection ◽  
High Chance ◽  
Selection Of ◽  
Design Steps

AbstractMotivationConceptually, epitope-based vaccine design poses two distinct problems: (1) selecting the best epitopes eliciting the strongest possible immune response, and (2) arranging and linking the selected epitopes through short spacer sequences to string-of-beads vaccines so as to increase the recovery likelihood of each epitope during antigen processing. Current state-of-the-art approaches solve this design problem sequentially. Consequently, such approaches are unable to capture the inter-dependencies between the two design steps, usually emphasizing theoretical immunogenicity over correct vaccine processing and resulting in vaccines with less effective immunogencity.ResultsIn this work, we present a computational approach based on linear programming that solves both design steps simultaneously, allowing to weigh the selection of a set of epitopes that have great immunogenic potential against their assembly into a string-of-beads construct that provides a high chance of recovery. We conducted Monte-Carlo cleavage simulations to show that, indeed, a fixed set of epitopes often cannot be assembled adequately, whereas selecting epitopes to accommodate proper cleavage requirements substantially improves their recovery probability and thus the effective immunogenicity, pathogen, and population coverage of the resulting vaccines by at least two fold.AvailabilityThe software and the data analyzed are available at https://github.com/SchubertLab/JessEV

scholarly journals Joint epitope selection and spacer design for string-of-beads vaccines

2020 ◽  
Vol 36 (Supplement_2) ◽  
pp. i643-i650
Author(s):  
Emilio Dorigatti ◽  
Benjamin Schubert
Keyword(s):  
Antigen Processing ◽  
State Of The Art ◽  
Supplementary Information ◽  
Current State ◽  
Fixed Set ◽  
Epitope Selection ◽  
High Chance ◽  
Selection Of ◽  
Design Steps

Abstract Motivation Conceptually, epitope-based vaccine design poses two distinct problems: (i) selecting the best epitopes to elicit the strongest possible immune response and (ii) arranging and linking them through short spacer sequences to string-of-beads vaccines, so that their recovery likelihood during antigen processing is maximized. Current state-of-the-art approaches solve this design problem sequentially. Consequently, such approaches are unable to capture the inter-dependencies between the two design steps, usually emphasizing theoretical immunogenicity over correct vaccine processing, thus resulting in vaccines with less effective immunogenicity in vivo. Results In this work, we present a computational approach based on linear programming, called JessEV, that solves both design steps simultaneously, allowing to weigh the selection of a set of epitopes that have great immunogenic potential against their assembly into a string-of-beads construct that provides a high chance of recovery. We conducted Monte Carlo cleavage simulations to show that a fixed set of epitopes often cannot be assembled adequately, whereas selecting epitopes to accommodate proper cleavage requirements substantially improves their recovery probability and thus the effective immunogenicity, pathogen and population coverage of the resulting vaccines by at least 2-fold. Availability and implementation The software and the data analyzed are available at https://github.com/SchubertLab/JessEV. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals BonMOLière: Small-Sized Libraries of Readily Purchasable Compounds, Optimized to Produce Genuine Hits in Biological Screens across the Protein Space

2021 ◽  
Vol 22 (15) ◽  
pp. 7773
Author(s):  
Neann Mathai ◽  
Conrad Stork ◽  
Johannes Kirchmair
Keyword(s):  
Large Scale ◽  
Computational Approach ◽  
Large Sets ◽  
Compound Libraries ◽  
Wide Range ◽  
Protein Space ◽  
High Chance ◽  
Large Scale Screening ◽  
Early Drug ◽  
Selection Of

Experimental screening of large sets of compounds against macromolecular targets is a key strategy to identify novel bioactivities. However, large-scale screening requires substantial experimental resources and is time-consuming and challenging. Therefore, small to medium-sized compound libraries with a high chance of producing genuine hits on an arbitrary protein of interest would be of great value to fields related to early drug discovery, in particular biochemical and cell research. Here, we present a computational approach that incorporates drug-likeness, predicted bioactivities, biological space coverage, and target novelty, to generate optimized compound libraries with maximized chances of producing genuine hits for a wide range of proteins. The computational approach evaluates drug-likeness with a set of established rules, predicts bioactivities with a validated, similarity-based approach, and optimizes the composition of small sets of compounds towards maximum target coverage and novelty. We found that, in comparison to the random selection of compounds for a library, our approach generates substantially improved compound sets. Quantified as the “fitness” of compound libraries, the calculated improvements ranged from +60% (for a library of 15,000 compounds) to +184% (for a library of 1000 compounds). The best of the optimized compound libraries prepared in this work are available for download as a dataset bundle (“BonMOLière”).

scholarly journals Soft Threshold Ternary Networks

2020 ◽  
Author(s):  
Weixiang Xu ◽  
Xiangyu He ◽  
Tianli Zhao ◽  
Qinghao Hu ◽  
Peisong Wang ◽  
...  
Keyword(s):  
Neural Networks ◽  
Mobile Devices ◽  
State Of The Art ◽  
Performance Gap ◽  
Training Time ◽  
Current State ◽  
The Arts ◽  
Soft Threshold ◽  
And Storage ◽  
Selection Of

Large neural networks are difficult to deploy on mobile devices because of intensive computation and storage. To alleviate it, we study ternarization, a balance between efficiency and accuracy that quantizes both weights and activations into ternary values. In previous ternarized neural networks, a hard threshold Δ is introduced to determine quantization intervals. Although the selection of Δ greatly affects the training results, previous works estimate Δ via an approximation or treat it as a hyper-parameter, which is suboptimal. In this paper, we present the Soft Threshold Ternary Networks (STTN), which enables the model to automatically determine quantization intervals instead of depending on a hard threshold. Concretely, we replace the original ternary kernel with the addition of two binary kernels at training time, where ternary values are determined by the combination of two corresponding binary values. At inference time, we add up the two binary kernels to obtain a single ternary kernel. Our method dramatically outperforms current state-of-the-arts, lowering the performance gap between full-precision networks and extreme low bit networks. Experiments on ImageNet with AlexNet (Top-1 55.6%), ResNet-18 (Top-1 66.2%) achieves new state-of-the-art.

scholarly journals OPWUM: Opportunistic MAC Protocol Leveraging Wake-Up Receivers in WSNs

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Fayçal Ait Aoudia ◽  
Matthieu Gautier ◽  
Olivier Berder
Keyword(s):  
Power Consumption ◽  
Analytical Study ◽  
State Of The Art ◽  
Mac Protocol ◽  
Promising Technique ◽  
Improve Energy Efficiency ◽  
Current State ◽  
Unreliable Links ◽  
Careful Design ◽  
Selection Of

Opportunistic forwarding has emerged as a promising technique to address the problem of unreliable links typical in wireless sensor networks and improve energy efficiency by exploiting multiuser diversity. Timer-based solutions, such as timer-based contention, form promising schemes to allow opportunistic next hop relay selection. However, they can incur significant idle listening and thus reduce the lifetime of the network. To tackle this problem, we propose to exploit emerging wake-up receiver technologies that have the potential to considerably reduce the power consumption of wireless communications. A careful design of MAC protocols is required to efficiently employ these new devices. In this work, we propose Opportunistic Wake-Up MAC (OPWUM), a novel multihop MAC protocol using timer-based contention. It enables the opportunistic selection of the best receiver among its neighboring nodes according to a given metric (e.g., the remaining energy), without requiring any knowledge about them. Moreover, OPWUM exploits emerging wake-up receivers to drastically reduce nodes power consumption. Through analytical study and exhaustive networks simulations, we show the effectiveness of OPWUM compared to the current state-of-the-art protocols using timer-based contention.

scholarly journals How to Model Tendon-Driven Continuum Robots and Benchmark Modelling Performance

2021 ◽  
Vol 7 ◽  
Author(s):  
Priyanka Rao ◽  
Quentin Peyron ◽  
Sven Lilge ◽  
Jessica Burgner-Kahrs
Keyword(s):  
Case Studies ◽  
State Of The Art ◽  
Computation Time ◽  
Comprehensive Overview ◽  
Continuum Robots ◽  
Current State ◽  
Selection Of ◽  
Modelling Approaches

Tendon actuation is one of the most prominent actuation principles for continuum robots. To date, a wide variety of modelling approaches has been derived to describe the deformations of tendon-driven continuum robots. Motivated by the need for a comprehensive overview of existing methodologies, this work summarizes and outlines state-of-the-art modelling approaches. In particular, the most relevant models are classified based on backbone representations and kinematic as well as static assumptions. Numerical case studies are conducted to compare the performance of representative modelling approaches from the current state-of-the-art, considering varying robot parameters and scenarios. The approaches show different performances in terms of accuracy and computation time. Guidelines for the selection of the most suitable approach for given designs of tendon-driven continuum robots and applications are deduced from these results.

Metrics in routing protocol for wireless mesh networks

2013 ◽  
Vol 18 (4) ◽  
pp. 7-20 ◽  
Author(s):  
Piotr Owczarek ◽  
Piotr Zwierzykowski
Keyword(s):  
Quality Assessment ◽  
Routing Protocol ◽  
Ad Hoc ◽  
Mesh Networks ◽  
State Of The Art ◽  
Routing Metrics ◽  
Wireless Mesh ◽  
Current State ◽  
Selection Of ◽  
Network Type

Abstract The interest in services offered by wireless network has been growing for many years. It has encouraged the development of wireless technologies. New solutions are able to satisfy the ever-increasing demands concerning wireless services. It is also evident in the diversification of quality assessment methods employed with reference to connections used in such networks. One of the basic elements used in connection quality assessment are metrics. The use of metrics is directly linked to the type of the routing protocol applied in a given network. The selection of a given routing protocol is often determined by its specific properties that might be advantageous in a certain network type, or that are important in terms of the type or scope of services provided. Therefore, it is easy to identify a relationship between metrics and the area of application of a given routing protocol. The significance and diversity of metrics is also reflected inWireless Mesh Networks (WMNs). The proposed paper presents a review of the current state-of-the-art routing metrics for Ad-hoc and WMN networks

Stochastic Process Model for the Optimization of a Rotorcraft with Categorical Variables

2014 ◽  
Vol 59 (4) ◽  
pp. 1-14 ◽  
Author(s):  
José Valenzuela del Río ◽  
Dimitri Mavris
Keyword(s):  
Stochastic Process ◽  
Process Model ◽  
State Of The Art ◽  
Categorical Variables ◽  
Efficient Global Optimization ◽  
Current State ◽  
Computationally Intensive ◽  
Search Design ◽  
Pareto Fronts ◽  
Selection Of

This paper proposes an improved stochastic process model for the selection of categorical variables, such as airfoils and materials, in rotorcraft design. This process leverages trends in typical rotorcraft conceptual design objectives that are similar across different categories. Also, this paper extends the use of efficient global optimization (EGO) algorithms, which intelligently search design spaces, to the previously proposed stochastic process thereby enabling the use of more computationally intensive tools earlier in the design process. To optimize the EGO infill criterion, a genetic algorithm is developed that is capable of searching domains with categorical variables. The proposed stochastic process model is successfully tested against traditional independent surrogates when approximating the engine shaft horsepower of the UH-60A with a choice of airfoils. Finally, a test to optimize the UH-60A engine shaft horsepower at two flight conditions demonstrates that the proposed extension of the EGO algorithm is more efficient at finding the Pareto fronts than the current state-of-the-art.

Conference Summary, Strategic Science Symposium

2003 ◽  
Vol 127 (5) ◽  
pp. 549-553 ◽  
Author(s):  
Richard J. Zarbo ◽  
M. Elizabeth H. Hammond
Keyword(s):  
State Of The Art ◽  
New Technology ◽  
Regulatory Compliance ◽  
Assessment Practice ◽  
Current State ◽  
Her 2 ◽  
Education Model ◽  
Billing And Coding ◽  
Science Symposium ◽  
Selection Of

Abstract Context.—Practicing pathologists often encounter controversial clinical issues and nonstandardized laboratory approaches to the evolving science of predictive/prognostic tumor marker assays. This dilemma becomes especially acute when the assay is the sole determinant for selection of a specific therapy. Objectives.—To summarize the areas of practical agreement and identify opportunities for improvement in Her-2/neu testing of breast cancer. Design.—The College of American Pathologists created a new comprehensive education model, called Strategic Science, with expert speakers integrating new and evolving basic, clinical, and scientific issues of Her-2/neu testing with aspects of laboratory management. Setting.—Symposium held May 4 and 5, 2002, in Rosemont, Ill. Participants.—Ten speakers and more than 100 attendees. Results.—Components addressed were new technology assessment, practice guidelines, quality assurance, regulatory compliance, risk and liability, billing and coding, cost analysis, consultation, information management, and results reporting. Conclusions.—This Strategic Science symposium derived areas of practical agreement, defined the current state-of-the-art, and identified areas for improvement in Her-2/neu testing.

scholarly journals Seed Selection Strategies for Overlap Detection

2018 ◽  
Author(s):  
Jonathan Teutenberg
Keyword(s):  
State Of The Art ◽  
Data Sets ◽  
Seed Selection ◽  
Selection Strategies ◽  
Current State ◽  
Long Read ◽  
Selection Of

AbstractThe current state-of-the-art assemblers of long, error-prone reads rely on detecting all-vs-all overlaps within the set of reads with overlaps represented by a sparse selection of short subsequences or “seeds”. Though the quality of selection of these seeds can impact both accuracy and speed of overlap detection, existing algorithms do little more than ignore over-represented seeds. Here we propose several more informed seed selection strategies to improve precision and recall of overlaps. These strategies are evaluated against real long-read data sets with a range of fixed seed sizes. We show that these strategies substantially improve the utility of individual seeds over uninformed selection.

scholarly journals A Review of Zein as a Potential Biopolymer for Tissue Engineering and Nanotechnological Applications

Processes ◽  
2020 ◽  
Vol 8 (11) ◽  
pp. 1376
Author(s):  
Carlos Joaquín Pérez-Guzmán ◽  
Roberto Castro-Muñoz
Keyword(s):  
Tissue Engineering ◽  
Review Paper ◽  
State Of The Art ◽  
Research Community ◽  
Anatomical Structure ◽  
Natural Origin ◽  
Current State ◽  
Current Alternative ◽  
The Right ◽  
Selection Of

Tissue engineering (TE) is one of the most challenging fields of research since it provides current alternative protocols and materials for the regeneration of damaged tissue. The success of TE has been mainly related to the right selection of nano-sized biocompatible materials for the development of matrixes, which can display excellent anatomical structure, functionality, mechanical properties, and histocompatibility. Today, the research community has paid particular attention to zein as a potential biomaterial for TE applications and nanotechnological approaches. Considering the properties of zein and the advances in the field, there is a need to reviewing the current state of the art of using this natural origin material for TE and nanotechnological applications. Therefore, the goal of this review paper is to elucidate the latest (over the last five years) applications and development works in the field, including TE, encapsulations of drugs, food, pesticides and bandaging for external wounds. In particular, attention has been focused on studies proving new breakthroughs and findings. Also, a complete background of zein’s properties and features are addressed.

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