scholarly journals Alignment-Free Genome Tree Inference by Learning Group-Specific Distance Metrics

2013 ◽  
Vol 5 (8) ◽  
pp. 1470-1484 ◽  
Author(s):  
Kaustubh R. Patil ◽  
Alice C. McHardy
Keyword(s):  
Distance Metrics ◽  
Learning Group ◽  
Alignment Free ◽  
Tree Inference ◽  
Genome Tree ◽  
Specific Distance

LearnMet: learning domain-specific distance metrics for plots of scientific functions

2007 ◽  
Vol 35 (1) ◽  
pp. 29-53
Author(s):  
Aparna Varde ◽  
Elke Rundensteiner ◽  
Carolina Ruiz ◽  
Mohammed Maniruzzaman ◽  
Richard Sisson
Keyword(s):  
Distance Metrics ◽  
Domain Specific ◽  
Specific Distance

scholarly journals Benchmarking of alignment-free sequence comparison methods

2019 ◽  
Author(s):  
Andrzej Zielezinski ◽  
Hani Z. Girgis ◽  
Guillaume Bernard ◽  
Chris-Andre Leimeister ◽  
Kujin Tang ◽  
...  
Keyword(s):  
Sequence Comparison ◽  
Regulatory Element ◽  
Gene Tree ◽  
Species Trees ◽  
Data Types ◽  
Data Intensive ◽  
Current State ◽  
Alignment Free ◽  
Tree Inference ◽  
Data Intensive Applications

ABSTRACTAlignment-free (AF) sequence comparison is attracting persistent interest driven by data-intensive applications. Hence, many AF procedures have been proposed in recent years, but a lack of a clearly defined benchmarking consensus hampers their performance assessment. Here, we present a community resource (http://afproject.org) to establish standards for comparing alignment-free approaches across different areas of sequence-based research. We characterize 74 AF methods available in 24 software tools for five research applications, namely, protein sequence classification, gene tree inference, regulatory element detection, genome-based phylogenetic inference and reconstruction of species trees under horizontal gene transfer and recombination events. The interactive web service allows researchers to explore the performance of alignment-free tools relevant to their data types and analytical goals. It also allows method developers to assess their own algorithms and compare them with current state-of-the-art tools, accelerating the development of new, more accurate AF solutions.

scholarly journals The Water-Energy Nexus at City Level: The Case Study of Skiathos

Proceedings ◽  
2018 ◽  
Vol 2 (11) ◽  
pp. 694
Author(s):  
Alexandra E. Ioannou ◽  
Chrysi S. Laspidou
Keyword(s):  
Time Series ◽  
Energy Consumption ◽  
Water Use ◽  
Distance Metrics ◽  
Human Needs ◽  
Water Energy Nexus ◽  
Basic Human Needs ◽  
Nexus Analysis ◽  
Specific Distance

Water and energy are two inextricably linked resources of great importance, as they are the key for satisfying basic human needs. In this study a water–energy nexus analysis is conducted in order to achieve a sustainable supply and effectively manage water and energy at city level. Different electricity uses such as domestic, agricultural and commercial are compared and tested on how they correlate with water use. Moreover, time series of water and energy consumption for the island of Skiathos are analyzed using specific distance metrics. The results of the analysis show that water and energy are intimately related.

A comment on geographically weighted regression with parameter-specific distance metrics

2019 ◽  
Vol 33 (7) ◽  
pp. 1289-1299 ◽  
Author(s):  
Taylor Oshan ◽  
Levi John Wolf ◽  
A. Stewart Fotheringham ◽  
Wei Kang ◽  
Ziqi Li ◽  
...  
Keyword(s):  
Geographically Weighted Regression ◽  
Weighted Regression ◽  
Distance Metrics ◽  
Specific Distance
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