Evidence map›Paper›PMID 26376976›Full record

ArticleBiology direct2015

KGCAK: a K-mer based database for genome-wide phylogeny and complexity evaluation.

Dapeng Wang, Jiayue Xu, Jun Yu

Abstract read
In one paragraph

Article in Biology direct, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Dapeng WangCAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, 100101, PR China. dapeng.wang@ucl.ac.uk.
Jiayue XuCAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, 100101, PR China. xujy@big.ac.cn.
Jun YuCAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, 100101, PR China. junyu@big.ac.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe K-mer approach, treating genomic sequences as simple characters and counting the relative abundance of each string upon a fixed K, has been extensively applied to phylogeny inference for genome assembly, annotation, and comparison.

resultsTo meet increasing demands for comparing large genome sequences and to promote the use of the K-mer approach, we develop a versatile database, KGCAK ( http://kgcak.big.ac.cn/KGCAK/ ), containing ~8,000 genomes that include genome sequences of diverse life forms (viruses, prokaryotes, protists, animals, and plants) and cellular organelles of eukaryotic lineages. It builds phylogeny based on genomic elements in an alignment-free fashion and provides in-depth data processing enabling users to compare the complexity of genome sequences based on K-mer distribution.

conclusionWe hope that KGCAK becomes a powerful tool for exploring relationship within and among groups of species in a tree of life based on genomic data.

Indexed as

Evolution, MolecularGenomePhylogenySequence Analysis, DNA

Identifiers

PMID26376976
PMCPMC4573299

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.