Fast sequence analysis based on diamond sampling.

Liangxin Gao, Wenzhen Bao, Hongbo Zhang, Chang-An Yuan, De-Shuang Huang

Abstract read

In one paragraph

Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

0cells of the map it votes in

0citing 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

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3 · Its place in the literature

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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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

5 authors.

Liangxin GaoInstitute of Machine Learning and Systems Biology, School of Electronics and Information Engineering, Tongji University, Shanghai, China.

Wenzhen BaoInstitute of Machine Learning and Systems Biology, School of Electronics and Information Engineering, Tongji University, Shanghai, China.

Hongbo ZhangInstitute of Machine Learning and Systems Biology, School of Electronics and Information Engineering, Tongji University, Shanghai, China.

Chang-An YuanScience Computing and Intelligent Information Processing of GuangXi Higher Education Key Laboratory, Guangxi Teachers Education University, Nanning, Guangxi, China.

De-Shuang HuangInstitute of Machine Learning and Systems Biology, School of Electronics and Information Engineering, Tongji University, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Both in DNA and protein contexts, an important method for modelling motifs is to utilize position weight matrix (PWM) in biological sequences. With the development of genome sequencing technology, the quantity of the sequence data is increasing explosively, so the faster searching algorithms which have the ability to meet the increasingly need are desired to develop. In this paper, we proposed a method for speeding up the searching process of candidate transcription factor binding sites (TFBS), and the users can be allowed to specify p threshold to get the desired trade-off between speed and sensitivity for a particular sequence analysis. Moreover, the proposed method can also be generalized to large-scale annotation and sequence projects.

Indexed as

Response ElementsSoftwareSequence Analysis, DNATranscription FactorsTranscription Factors

Identifiers

PMID29953448

DOI10.1371/journal.pone.0198922

PMCPMC6023231

What OpenQuestion holds

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LicenceCC BY

Read underepoch 390

Registered trials

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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.