Fig 6 - Computing generalized cophenetic distances under all Lp norms: A near-linear time algorithmic framework

(Cont. from <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1013069#pcbi.1013069.g005" target="_blank">Fig 5</a>). Sampled distribution of three cophenetic distances is shown for Lp&l...

Full description

Saved in:

Bibliographic Details
Main Author:	Paweł Górecki (3285255) (author)
Other Authors:	Alexey Markin (16698687) (author), Sriram Vijendran (21520036) (author), Oliver Eulenstein (3291621) (author)
Published:	2025
Subjects:	Biophysics Microbiology Genetics Molecular Biology Biotechnology Cancer Infectious Diseases Space Science Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified linear time complexity e ., naïve incorporating generalized variants >< sub >< div >< p unrestricted algorithmic framework new algorithmic framework >< sub xmlns generalized cophenetic distances generalized class ></ sub p </ cophenetic distances widely recognized vector format trees represented significantly restricts scale trees scale applications scalability study quadratic runtime practical performance l </ key components established metric dates back current best compare pairs biology used become prohibitive analyze trees also enhances 60 years
Tags:	Add Tag No Tags, Be the first to tag this record!

Be the first to leave a comment!

Fig 6 - Computing generalized cophenetic distances under all <i>L</i><sub><i>p</i></sub> norms: A near-linear time algorithmic framework

Similar Items