scholarly journals A phylogenetic approach for weighting genetic sequences

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Nicola De Maio ◽  
Alexander V. Alekseyenko ◽  
William J. Coleman-Smith ◽  
Fabio Pardi ◽  
Marc A. Suchard ◽  
...  
Keyword(s):  
Sequence Alignment ◽  
Frequency Estimation ◽  
Protein Family ◽  
Computationally Efficient ◽  
Alignment Column ◽  
Weighting Schemes ◽  
Genetic Sequences ◽  
Sequence Logos ◽  
Computationally Efficient Algorithms ◽  
Measuring Sequence

Abstract Background Many important applications in bioinformatics, including sequence alignment and protein family profiling, employ sequence weighting schemes to mitigate the effects of non-independence of homologous sequences and under- or over-representation of certain taxa in a dataset. These schemes aim to assign high weights to sequences that are ‘novel’ compared to the others in the same dataset, and low weights to sequences that are over-represented. Results We formalise this principle by rigorously defining the evolutionary ‘novelty’ of a sequence within an alignment. This results in new sequence weights that we call ‘phylogenetic novelty scores’. These scores have various desirable properties, and we showcase their use by considering, as an example application, the inference of character frequencies at an alignment column—important, for example, in protein family profiling. We give computationally efficient algorithms for calculating our scores and, using simulations, show that they are versatile and can improve the accuracy of character frequency estimation compared to existing sequence weighting schemes. Conclusions Our phylogenetic novelty scores can be useful when an evolutionarily meaningful system for adjusting for uneven taxon sampling is desired. They have numerous possible applications, including estimation of evolutionary conservation scores and sequence logos, identification of targets in conservation biology, and improving and measuring sequence alignment accuracy.

scholarly journals Phylogenetic Novelty Scores: a New Approach for Weighting Genetic Sequences

2020 ◽  
Author(s):  
Nicola De Maio ◽  
Alexander V. Alekseyenko ◽  
William J. Coleman-Smith ◽  
Fabio Pardi ◽  
Marc A. Suchard ◽  
...  
Keyword(s):  
Sequence Alignment ◽  
Frequency Estimation ◽  
Protein Family ◽  
Computationally Efficient ◽  
New Approach ◽  
Alignment Column ◽  
Weighting Schemes ◽  
Genetic Sequences ◽  
Sequence Logos ◽  
Computationally Efficient Algorithms

AbstractBackgroundMany important applications in bioinformatics, including sequence alignment and protein family profiling, employ sequence weighting schemes to mitigate the effects of non-independence of homologous sequences and under- or over-representation of certain taxa in a dataset. These schemes aim to assign high weights to sequences that are ‘novel’ compared to the others in the same dataset, and low weights to sequences that are over-represented.ResultsWe formalise this principle by rigorously defining the evolutionary ‘novelty’ of a sequence within an alignment. This results in new sequence weights that we call ‘phylogenetic novelty scores’. These scores have various desirable properties, and we showcase their use by considering, as an example application, the inference of character frequencies at an alignment column — important, for example, in protein family profiling. We give computationally efficient algorithms for calculating our scores and, using simulations, show that they improve the accuracy of character frequency estimation compared to existing sequence weighting schemes.ConclusionsOur phylogenetic novelty scores can be useful when an evolutionarily meaningful system for adjusting for uneven taxon sampling is desired. They have numerous possible applications, including estimation of evolutionary conservation scores and sequence logos, identification of targets in conservation biology, and improving and measuring sequence alignment accuracy.

Computationally efficient algorithms for location area planning in future cellular systems

2000 ◽  
Vol 23 (13) ◽  
pp. 1263-1280 ◽  
Author(s):  
P. Demestichas ◽  
N. Georgantas ◽  
E. Tzifa ◽  
V. Demesticha ◽  
M. Striki ◽  
...  
Keyword(s):  
Efficient Algorithms ◽  
Cellular Systems ◽  
Computationally Efficient ◽  
Location Area ◽  
Computationally Efficient Algorithms ◽  
Area Planning

scholarly journals Characterizing Longitudinal Changes in the Impedance Spectra of In-Vivo Peripheral Nerve Electrodes

Micromachines ◽  
2018 ◽  
Vol 9 (11) ◽  
pp. 587 ◽  
Author(s):  
Malgorzata Straka ◽  
Benjamin Shafer ◽  
Srikanth Vasudevan ◽  
Cristin Welle ◽  
Loren Rieth
Keyword(s):  
Electrochemical Impedance ◽  
Iridium Oxide ◽  
Support Vector ◽  
Impedance Spectra ◽  
Computationally Efficient ◽  
Wide Range ◽  
Tissue Interface ◽  
Computationally Efficient Algorithms ◽  
Physical Changes

Characterizing the aging processes of electrodes in vivo is essential in order to elucidate the changes of the electrode–tissue interface and the device. However, commonly used impedance measurements at 1 kHz are insufficient for determining electrode viability, with measurements being prone to false positives. We implanted cohorts of five iridium oxide (IrOx) and six platinum (Pt) Utah arrays into the sciatic nerve of rats, and collected the electrochemical impedance spectroscopy (EIS) up to 12 weeks or until array failure. We developed a method to classify the shapes of the magnitude and phase spectra, and correlated the classifications to circuit models and electrochemical processes at the interface likely responsible. We found categories of EIS characteristic of iridium oxide tip metallization, platinum tip metallization, tip metal degradation, encapsulation degradation, and wire breakage in the lead. We also fitted the impedance spectra as features to a fine-Gaussian support vector machine (SVM) algorithm for both IrOx and Pt tipped arrays, with a prediction accuracy for categories of 95% and 99%, respectively. Together, this suggests that these simple and computationally efficient algorithms are sufficient to explain the majority of variance across a wide range of EIS data describing Utah arrays. These categories were assessed over time, providing insights into the degradation and failure mechanisms for both the electrode–tissue interface and wire bundle. Methods developed in this study will allow for a better understanding of how EIS can characterize the physical changes to electrodes in vivo.

A Model-Based Computationally Efficient Method for On-Line Detection of Chatter in Milling

2013 ◽  
Vol 135 (3) ◽  
Author(s):  
Lei Ma ◽  
Shreyes N. Melkote ◽  
James B. Castle
Keyword(s):  
Cutting Force ◽  
Efficient Method ◽  
Frequency Estimation ◽  
Chip Thickness ◽  
Computationally Efficient ◽  
Model Based ◽  
Chatter Suppression ◽  
Force Signal ◽  
Regeneration Effect ◽  
Milling Chatter

This paper presents a model-based computationally efficient method for detecting milling chatter in its incipient stages and for chatter frequency estimation by monitoring the cutting force signals. Based on a complex exponentials model for the dynamic chip thickness, the chip regeneration effect is amplified and isolated from the cutting force signal for early chatter detection. The proposed method is independent of the cutting conditions. With the aid of a one tap adaptive filter, the method is shown to be capable of distinguishing between chatter and the dynamic transients in the cutting forces arising from sudden changes in workpiece geometry and tool entry/exit. To facilitate chatter suppression once the onset of chatter is detected, a time domain algorithm is proposed so that the dominant chatter frequency can be accurately determined without using computationally expensive frequency domain transforms such as the Fourier transform. The proposed method is experimentally validated.

Development of a Self-Contained Sensor Bearing for Rail Applications

2002 ◽  
Author(s):  
Michael L. French ◽  
Samuel R. Williams
Keyword(s):  
Wireless Communication ◽  
Laboratory Test ◽  
Mechanical System ◽  
Test Data ◽  
Vibration Analysis ◽  
Communication Channel ◽  
System Development ◽  
Vibration Signal ◽  
Computationally Efficient ◽  
Computationally Efficient Algorithms

This paper discusses bearing borne sensor system development efforts for use in monitoring the rail bearing and connected mechanical system. The measurement of speed, temperature, and vibration are considered. In the area of vibration analysis, particular emphasis is placed on the use of computationally efficient algorithms for use in parameterization of the vibration signal. Results from laboratory test data are presented. Finally, the relative merits of a wired versus a wireless communication channel, at the bearing level, are discussed.

Determining Feasible Robot Placements in Robotic Cells for Composite Prepreg Sheet Layup

2019 ◽  
Author(s):  
Rishi K. Malhan ◽  
Ariyan M. Kabir ◽  
Brual Shah ◽  
Timotei Centea ◽  
Satyandra K. Gupta
Keyword(s):  
High Performance ◽  
Computationally Efficient ◽  
Robotic Cell ◽  
Precursor Material ◽  
Robotic Cells ◽  
A Cell ◽  
Complex Decision ◽  
Computationally Efficient Algorithms ◽  
Refinement Strategy ◽  
Robot Placement

Abstract High-performance composites are widely used in industry because of specific mechanical properties and lightweighting opportunities. Current automation solutions to manufacturing components from prepreg (pre-impregnated precursor material) sheets are limited. Our previous work has demonstrated the technical feasibility of a robotic cell to automate the sheet layup process. Many decisions are required for the cell to function correctly, and the time necessary to make these decisions must be reduced to utilize the cell effectively. Robot placement with respect to the mold is a significant and complex decision problem. Ensuring that robots can collaborate effectively requires addressing multiple constraints related to the robot workspace, singularity, and velocities. Solving this problem requires developing computationally efficient algorithms to find feasible robot placements in the cell. We describe an approach based on successive solution refinement strategy to identify a cell design that satisfies all constraints related to robot placement.

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