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ZENODO
Software . 2024
License: CC BY
Data sources: ZENODO
ZENODO
Software . 2024
License: CC BY
Data sources: Datacite
ZENODO
Software . 2024
License: CC BY
Data sources: Datacite
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philosopi-everthine/philosopi-public: philosopi-public v1.0.0-alpha

integration_instructionsResearch softwarekeyboard_double_arrow_right Software 17 Jul 2024Publisher:Zenodo
Authors: philosopi-everthine;
Code repository: https://github.com/philosopi-everthine/philosopi-public/tree/PHILOSOPI

doi: 10.5281/zenodo.12754369 , 10.5281/zenodo.12754368

philosopi-everthine/philosopi-public: philosopi-public v1.0.0-alpha

Abstract

PHILOSOPI (Protein Homolog Islands Landscape Organization for Sequence Origin and Profile Indexing) is a protein sequence clustering and indexing method for comparative profiling. Here we provide a heuristic algorithm of neighborhood analysis in PHILOSOPI. This simple source code is wrtten in python3. Prerequisites Python 3.11 (https://www.python.org/) Numpy 1.24.2 (https://numpy.org/) Clustalo 1.2.2 (http://www.clustal.org/omega/) How to Use (Command line) python3 "neighborhood-analysis.py" -i distmat.txt -o output_edges.txt

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    popularity
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    influence
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average