Discovery of salivary gland tumors’ biomarkers via co-regularized sparse-group lasso

S. Imangaliyev; J.H. Matse; J.G.M. Bolscher; R.H. Brakenhoff; D.T.W. Wong; E. Bloemena; E.C.I. Veerman; E. Levin

doi:10.1007/978-3-319-67786-6_21

Discovery of salivary gland tumors’ biomarkers via co-regularized sparse-group lasso

S. Imangaliyev, J.H. Matse, J.G.M. Bolscher, R.H. Brakenhoff, D.T.W. Wong, E. Bloemena, E.C.I. Veerman, E. Levin

Research output: Chapter in Book / Report / Conference proceeding › Conference contribution › Academic › peer-review

Abstract

In this study, we discovered a panel of discriminative microRNAs in salivary gland tumors by application of statistical machine learning methods. We modelled multi-component interactions of salivary microRNAs to detect group-based associations among the features, enabling the distinction of malignant from benign tumors with a high predictive performance utilizing only seven microRNAs. Several of the identified microRNAs are separately known to be involved in cell cycle regulation. Integrated biological interpretation of identified microRNAs can provide potential new insights into the biology of salivary gland tumors and supports the development of non-invasive diagnostic tests to discriminate salivary gland tumor subtypes.

Original language	English
Title of host publication	Discovery Science
Subtitle of host publication	20th International Conference, DS 2017, Kyoto, Japan, October 15–17, 2017 : proceedings
Editors	A. Yamamoto, T. Kida, T. Uno, T. Kuboyama
Place of Publication	Cham
Publisher	Springer
Pages	298-305
Number of pages	8
ISBN (Electronic)	9783319677866
ISBN (Print)	9783319677859
DOIs	https://doi.org/10.1007/978-3-319-67786-6_21
Publication status	Published - 2017
Event	20th International Conference on Discovery Science, DS 2017 - Kyoto, Japan Duration: 15 Oct 2017 → 17 Oct 2017

Conference

Conference	20th International Conference on Discovery Science, DS 2017
Country/Territory	Japan
City	Kyoto
Period	15/10/17 → 17/10/17

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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Imangaliyev, S., Matse, J. H., Bolscher, J. G. M., Brakenhoff, R. H., Wong, D. T. W., Bloemena, E., Veerman, E. C. I., & Levin, E. (2017). Discovery of salivary gland tumors’ biomarkers via co-regularized sparse-group lasso. In A. Yamamoto, T. Kida, T. Uno, & T. Kuboyama (Eds.), Discovery Science: 20th International Conference, DS 2017, Kyoto, Japan, October 15–17, 2017 : proceedings (pp. 298-305). Springer. https://doi.org/10.1007/978-3-319-67786-6_21

@inproceedings{1050da8d59674f8d92756e78fe8a549a,

title = "Discovery of salivary gland tumors{\textquoteright} biomarkers via co-regularized sparse-group lasso",

abstract = "In this study, we discovered a panel of discriminative microRNAs in salivary gland tumors by application of statistical machine learning methods. We modelled multi-component interactions of salivary microRNAs to detect group-based associations among the features, enabling the distinction of malignant from benign tumors with a high predictive performance utilizing only seven microRNAs. Several of the identified microRNAs are separately known to be involved in cell cycle regulation. Integrated biological interpretation of identified microRNAs can provide potential new insights into the biology of salivary gland tumors and supports the development of non-invasive diagnostic tests to discriminate salivary gland tumor subtypes.",

author = "S. Imangaliyev and J.H. Matse and J.G.M. Bolscher and R.H. Brakenhoff and D.T.W. Wong and E. Bloemena and E.C.I. Veerman and E. Levin",

year = "2017",

doi = "10.1007/978-3-319-67786-6_21",

language = "English",

isbn = "9783319677859",

pages = "298--305",

editor = "A. Yamamoto and T. Kida and T. Uno and T. Kuboyama",

booktitle = "Discovery Science",

publisher = "Springer",

note = "20th International Conference on Discovery Science, DS 2017 ; Conference date: 15-10-2017 Through 17-10-2017",

}

Imangaliyev, S, Matse, JH, Bolscher, JGM, Brakenhoff, RH, Wong, DTW, Bloemena, E, Veerman, ECI & Levin, E 2017, Discovery of salivary gland tumors’ biomarkers via co-regularized sparse-group lasso. in A Yamamoto, T Kida, T Uno & T Kuboyama (eds), Discovery Science: 20th International Conference, DS 2017, Kyoto, Japan, October 15–17, 2017 : proceedings. Springer, Cham, pp. 298-305, 20th International Conference on Discovery Science, DS 2017, Kyoto, Japan, 15/10/17. https://doi.org/10.1007/978-3-319-67786-6_21

Discovery of salivary gland tumors’ biomarkers via co-regularized sparse-group lasso. / Imangaliyev, S.; Matse, J.H.; Bolscher, J.G.M. et al.

Discovery Science: 20th International Conference, DS 2017, Kyoto, Japan, October 15–17, 2017 : proceedings. ed. / A. Yamamoto; T. Kida; T. Uno; T. Kuboyama. Cham : Springer, 2017. p. 298-305.

Research output: Chapter in Book / Report / Conference proceeding › Conference contribution › Academic › peer-review

TY - GEN

T1 - Discovery of salivary gland tumors’ biomarkers via co-regularized sparse-group lasso

AU - Imangaliyev, S.

AU - Matse, J.H.

AU - Bolscher, J.G.M.

AU - Brakenhoff, R.H.

AU - Wong, D.T.W.

AU - Bloemena, E.

AU - Veerman, E.C.I.

AU - Levin, E.

PY - 2017

Y1 - 2017

N2 - In this study, we discovered a panel of discriminative microRNAs in salivary gland tumors by application of statistical machine learning methods. We modelled multi-component interactions of salivary microRNAs to detect group-based associations among the features, enabling the distinction of malignant from benign tumors with a high predictive performance utilizing only seven microRNAs. Several of the identified microRNAs are separately known to be involved in cell cycle regulation. Integrated biological interpretation of identified microRNAs can provide potential new insights into the biology of salivary gland tumors and supports the development of non-invasive diagnostic tests to discriminate salivary gland tumor subtypes.

AB - In this study, we discovered a panel of discriminative microRNAs in salivary gland tumors by application of statistical machine learning methods. We modelled multi-component interactions of salivary microRNAs to detect group-based associations among the features, enabling the distinction of malignant from benign tumors with a high predictive performance utilizing only seven microRNAs. Several of the identified microRNAs are separately known to be involved in cell cycle regulation. Integrated biological interpretation of identified microRNAs can provide potential new insights into the biology of salivary gland tumors and supports the development of non-invasive diagnostic tests to discriminate salivary gland tumor subtypes.

U2 - 10.1007/978-3-319-67786-6_21

DO - 10.1007/978-3-319-67786-6_21

M3 - Conference contribution

SN - 9783319677859

SP - 298

EP - 305

BT - Discovery Science

A2 - Yamamoto, A.

A2 - Kida, T.

A2 - Uno, T.

A2 - Kuboyama, T.

PB - Springer

CY - Cham

T2 - 20th International Conference on Discovery Science, DS 2017

Y2 - 15 October 2017 through 17 October 2017

ER -

Imangaliyev S, Matse JH, Bolscher JGM, Brakenhoff RH, Wong DTW, Bloemena E et al. Discovery of salivary gland tumors’ biomarkers via co-regularized sparse-group lasso. In Yamamoto A, Kida T, Uno T, Kuboyama T, editors, Discovery Science: 20th International Conference, DS 2017, Kyoto, Japan, October 15–17, 2017 : proceedings. Cham: Springer. 2017. p. 298-305 doi: 10.1007/978-3-319-67786-6_21

Discovery of salivary gland tumors’ biomarkers via co-regularized sparse-group lasso

Abstract

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UN SDGs

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