DHSpred: support-vector-machine-based human DNase I hypersensitive sites prediction using the optimal features selected by random forest. (Q49403730)

20 February 2018

title

DHSpred: support-vector-machine-based human DNase I hypersensitive sites prediction using the optimal features selected by random forest. (English)

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20 February 2018

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support vector machine

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inferred from title

author name string

Balachandran Manavalan

series ordinal

1

1 reference

20 February 2018

Tae Hwan Shin

series ordinal

2

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20 February 2018

Gwang Lee

series ordinal

3

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20 February 2018

language of work or name

English

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publication date

8 December 2017

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20 February 2018

published in

Oncotarget

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20 February 2018

volume

9

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20 February 2018

issue

2

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20 February 2018

page(s)

1944-1956

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20 February 2018

describes a project that uses

scikit-learn

object named as

scikit-learn

1 reference

CZ Software Mentions: A large dataset of software mentions in the biomedical literature

scikit-learn

0 references

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Prediction of DNase I hypersensitive sites by using pseudo nucleotide compositions.

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14 August 2018

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14 August 2018

1 reference

PubMed

https://pubmed.ncbi.nlm.nih.gov/29416743

12 December 2020

inferred from PubMed ID database lookup

Mapping DNase-I hypersensitive sites on human isochores

1 reference

PubMed

https://pubmed.ncbi.nlm.nih.gov/29416743

12 December 2020

inferred from PubMed ID database lookup

iATC-mISF: a multi-label classifier for predicting the classes of anatomical therapeutic chemicals

1 reference

PubMed

https://pubmed.ncbi.nlm.nih.gov/29416743

12 December 2020

inferred from PubMed ID database lookup

Identifiers

DOI

10.18632/ONCOTARGET.23099

1 reference

20 February 2018

PMCID

5788611

1 reference

20 February 2018

PubMed ID

29416743

1 reference

20 February 2018