Comparative Study of Classification Algorithms for Various DNA Microarray Data.

Jingeun Kim, Yourim Yoon, Hye-Jin Park, Yong-Hyuk Kim

Open access · goldAbstract read

In one paragraph

Article in Genes, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it

0cells of the map it votes in

1citing papers in PubMed

1.4field-weighted citation impact, top 20% of its field

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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

1 citing paper in PubMed, 16 citations in OpenAlex.

Critical gene network and signaling pathway analysis of the extracellular signal-regulated kinase (ERK) pathway in ischemic stroke.Frontiers in molecular neuroscience · 2025
Article

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

4 authors at 2 institutions in 2 countries.

Jingeun KimDepartment of IT Convergence Engineering, Gachon University, Seongnam-daero 1342, Seongnam-si 13120, Korea.ORCID 0000-0001-7002-6650

Yourim YoonDepartment of Computer Engineering, College of Information Technology, Gachon University, Seongnam-daero 1342, Sujeong-gu, Seongnam-si 13120, Korea.ORCID 0000-0001-5875-0275

Hye-Jin ParkDepartment of Food Science and Biotechnology, College of BioNano Technology, Gachon University, Seongnam-daero 1342, Sujeong-gu, Seongnam-si 13120, Korea.

Yong-Hyuk KimSchool of Software, Kwangwoon University, 20 Kwangwoon-ro, Nowon-gu, Seoul 01897, Korea.ORCID 0000-0002-0492-0889

Gachon University · KRUniversity of Wisconsin–Madison · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Microarrays are applications of electrical engineering and technology in biology that allow simultaneous measurement of expression of numerous genes, and they can be used to analyze specific diseases. This study undertakes classification analyses of various microarrays to compare the performances of classification algorithms over different data traits. The datasets were classified into test and control groups based on five utilized machine learning methods, including MultiLayer Perceptron (MLP), Support Vector Machine (SVM), Decision Tree (DT), Random Forest (RF), and

Indexed as

AlgorithmsSupport Vector MachineMachine LearningNeural Networks, ComputerOligonucleotide Array Sequence Analysisclassificationdecision treek-nearest neighborsmachine learningmicroarraymultilayer perceptronrandom forestsupport vector machine

Identifiers

PMID35328048

DOI10.3390/genes13030494

PMCPMC8951024

OpenAlexW4220654285

What OpenQuestion holds

Textmetadata

LicenceCC BY

Read underepoch 390

Registered trials

None linked

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.