COMPARATIVE OF SUCCESS OF KNN WITH NEW PROPOSED K-SPLIT METHOD AND STRATIFIED CROSS VALIDATION ON REMOTE HOMOLOGUE PROTEIN DETECTION

Fahriye Gemci; Turgay İbrikçi; Ulus Çevik

doi:10.18038/estubtda.970169

TR EN

COMPARATIVE OF SUCCESS OF KNN WITH NEW PROPOSED K-SPLIT METHOD AND STRATIFIED CROSS VALIDATION ON REMOTE HOMOLOGUE PROTEIN DETECTION

Abstract

In this study, a remote homologous protein detection problem, which is a problem related to the field of bioinformatics and has made a great contribution in the field of medicine, is discussed. Protein sequences taken from the SCOP database, which is an important and widely used database for proteins, were tested for remote homologue protein detection in this study. Feature vectors were obtained from the protein sequences using the bag-of-words model. These obtained feature vectors were classified using the k-nearest Neighbor classifier algorithm. In this classification, the different distances used were Bray Curtis, Euclidean, Minkowski, Dice, Jaccard, Chebyshev, Cosine, SokalSneath, correlation, matching coefficient, RogersTanimoto, SokalMichener, Canbera, Hamming, Kulczynski, and RussellRao on the k-nearest Neighbor classifier for remote homologue protein detection. Two different new methods is proposed for preventing the imbalanced data problem. The first of these is special k-fold value and the other is novel k-split method. It is observed that the k-nearest Neighbor algorithm with the Bray Curtis distance and cross validation with special k-fold value and novel k-split method show the most successful performance, with 98.9% and 83.8% accuracy and 77% and 92% ROC score, respectively.

Keywords

Remote Homologue Protein, k-nearest Neighbor, Bag-of-words model, Distances, k-fold Stratified Cross Validation

COMPARATIVE OF SUCCESS OF KNN WITH NEW PROPOSED K-SPLIT METHOD AND STRATIFIED CROSS VALIDATION ON REMOTE HOMOLOGUE PROTEIN DETECTION

Abstract

In this study, a remote homologous protein detection problem, which is a problem belonging to the field of bioinformatics, which has a great contribution in the field of medicine, is discussed. Protein sequences taken from the SCOP database, which is an important and widely used database for proteins, were tested for remote homolog protein detection in this study. Feature vectors were obtained from the protein sequences using the bag of word model. These obtained feature vectors were classified using the kNN classifier algorithm. In this classification, the different distances were used as Bray Curtis, Chebyshev, Cosine, Dice, Euclidean, Hamming, Jaccard, Kulczynski, Matching coefficient, Minkowski, RogersTanimoto, RussellRao and SokalMichener on kNN classifier for remote homolog protein detection. There is proposed special k fold value formula for prevent imbalanced data problem. It has observed that the kNN algorithm with the Bray Curtis distance with cross validation with special k fold value shows the most successful performance with 99% accuracy.

Keywords

Remote Homolog Protein, k-nearest Neighbor (kNN), Bag of words model, Distances, k-fold Cross Validation

Supporting Institution

Çukurova University Scientific Research Projects (BAP)

Project Number

Project No: FDK-2019-11621.

References

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Details

Primary Language

English

Subjects

Engineering

Journal Section

Research Article

Authors

Fahriye Gemci ^*
0000-0003-0961-5266
Türkiye

Turgay İbrikçi This is me
0000-0003-1321-2523
Türkiye

Ulus Çevik This is me
0000-0002-0956-9725
Türkiye

Publication Date

March 30, 2022

Submission Date

July 12, 2021

Acceptance Date

March 24, 2022

Published in Issue

Year 2022 Volume: 23 Number: 1

DOI

https://doi.org/10.18038/estubtda.970169

IZ

https://izlik.org/JA25YB59GS

APA

Gemci, F., İbrikçi, T., & Çevik, U. (2022). COMPARATIVE OF SUCCESS OF KNN WITH NEW PROPOSED K-SPLIT METHOD AND STRATIFIED CROSS VALIDATION ON REMOTE HOMOLOGUE PROTEIN DETECTION. Eskişehir Technical University Journal of Science and Technology A - Applied Sciences and Engineering, 23(1), 87-108. https://doi.org/10.18038/estubtda.970169

AMA

1.Gemci F, İbrikçi T, Çevik U. COMPARATIVE OF SUCCESS OF KNN WITH NEW PROPOSED K-SPLIT METHOD AND STRATIFIED CROSS VALIDATION ON REMOTE HOMOLOGUE PROTEIN DETECTION. Estuscience - Se. 2022;23(1):87-108. doi:10.18038/estubtda.970169

Chicago

Gemci, Fahriye, Turgay İbrikçi, and Ulus Çevik. 2022. “COMPARATIVE OF SUCCESS OF KNN WITH NEW PROPOSED K-SPLIT METHOD AND STRATIFIED CROSS VALIDATION ON REMOTE HOMOLOGUE PROTEIN DETECTION”. Eskişehir Technical University Journal of Science and Technology A - Applied Sciences and Engineering 23 (1): 87-108. https://doi.org/10.18038/estubtda.970169.

EndNote

Gemci F, İbrikçi T, Çevik U (March 1, 2022) COMPARATIVE OF SUCCESS OF KNN WITH NEW PROPOSED K-SPLIT METHOD AND STRATIFIED CROSS VALIDATION ON REMOTE HOMOLOGUE PROTEIN DETECTION. Eskişehir Technical University Journal of Science and Technology A - Applied Sciences and Engineering 23 1 87–108.

IEEE

[1]F. Gemci, T. İbrikçi, and U. Çevik, “COMPARATIVE OF SUCCESS OF KNN WITH NEW PROPOSED K-SPLIT METHOD AND STRATIFIED CROSS VALIDATION ON REMOTE HOMOLOGUE PROTEIN DETECTION”, Estuscience - Se, vol. 23, no. 1, pp. 87–108, Mar. 2022, doi: 10.18038/estubtda.970169.

ISNAD

Gemci, Fahriye - İbrikçi, Turgay - Çevik, Ulus. “COMPARATIVE OF SUCCESS OF KNN WITH NEW PROPOSED K-SPLIT METHOD AND STRATIFIED CROSS VALIDATION ON REMOTE HOMOLOGUE PROTEIN DETECTION”. Eskişehir Technical University Journal of Science and Technology A - Applied Sciences and Engineering 23/1 (March 1, 2022): 87-108. https://doi.org/10.18038/estubtda.970169.

JAMA

1.Gemci F, İbrikçi T, Çevik U. COMPARATIVE OF SUCCESS OF KNN WITH NEW PROPOSED K-SPLIT METHOD AND STRATIFIED CROSS VALIDATION ON REMOTE HOMOLOGUE PROTEIN DETECTION. Estuscience - Se. 2022;23:87–108.

MLA

Gemci, Fahriye, et al. “COMPARATIVE OF SUCCESS OF KNN WITH NEW PROPOSED K-SPLIT METHOD AND STRATIFIED CROSS VALIDATION ON REMOTE HOMOLOGUE PROTEIN DETECTION”. Eskişehir Technical University Journal of Science and Technology A - Applied Sciences and Engineering, vol. 23, no. 1, Mar. 2022, pp. 87-108, doi:10.18038/estubtda.970169.

Vancouver

1.Fahriye Gemci, Turgay İbrikçi, Ulus Çevik. COMPARATIVE OF SUCCESS OF KNN WITH NEW PROPOSED K-SPLIT METHOD AND STRATIFIED CROSS VALIDATION ON REMOTE HOMOLOGUE PROTEIN DETECTION. Estuscience - Se. 2022 Mar. 1;23(1):87-108. doi:10.18038/estubtda.970169

COMPARATIVE OF SUCCESS OF KNN WITH NEW PROPOSED K-SPLIT METHOD AND STRATIFIED CROSS VALIDATION ON REMOTE HOMOLOGUE PROTEIN DETECTION

Abstract

Keywords

COMPARATIVE OF SUCCESS OF KNN WITH NEW PROPOSED K-SPLIT METHOD AND STRATIFIED CROSS VALIDATION ON REMOTE HOMOLOGUE PROTEIN DETECTION

Abstract

Keywords

Supporting Institution

Project Number

References

Details

Primary Language

Subjects

Journal Section

Authors

Publication Date

Submission Date

Acceptance Date

Published in Issue

DOI

IZ

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