Standard

Protein remote homology detection using dissimilarity-based multiple instance learning. / Mensi, Antonelli ; Bicego, Manuele; Lovato, Pietro; Loog, Marco; Tax, David M.J.

Structural, Syntactic, and Statistical Pattern Recognition : Joint IAPR International Workshop, S+SSPR 2018, Proceedings. ed. / X. Bai; E.R. Hancock; T.K. Ho; R.C. Wilson; B. Biggio; A. Robles-Kelly. Cham : Springer, 2018. p. 119-129 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11004 ).

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Harvard

Mensi, A, Bicego, M, Lovato, P, Loog, M & Tax, DMJ 2018, Protein remote homology detection using dissimilarity-based multiple instance learning. in X Bai, ER Hancock, TK Ho, RC Wilson, B Biggio & A Robles-Kelly (eds), Structural, Syntactic, and Statistical Pattern Recognition : Joint IAPR International Workshop, S+SSPR 2018, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11004 , Springer, Cham, pp. 119-129, Joint IAPR International Workshops on Structural and Syntactic Pattern Recognition, SSPR 2018 and Statistical Techniques in Pattern Recognition, SPR 2018, Beijing, China, 17/08/18. https://doi.org/10.1007/978-3-319-97785-0_12

APA

Mensi, A., Bicego, M., Lovato, P., Loog, M., & Tax, D. M. J. (2018). Protein remote homology detection using dissimilarity-based multiple instance learning. In X. Bai, E. R. Hancock, T. K. Ho, R. C. Wilson, B. Biggio, & A. Robles-Kelly (Eds.), Structural, Syntactic, and Statistical Pattern Recognition : Joint IAPR International Workshop, S+SSPR 2018, Proceedings (pp. 119-129). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11004 ). Cham: Springer. https://doi.org/10.1007/978-3-319-97785-0_12

Vancouver

Mensi A, Bicego M, Lovato P, Loog M, Tax DMJ. Protein remote homology detection using dissimilarity-based multiple instance learning. In Bai X, Hancock ER, Ho TK, Wilson RC, Biggio B, Robles-Kelly A, editors, Structural, Syntactic, and Statistical Pattern Recognition : Joint IAPR International Workshop, S+SSPR 2018, Proceedings. Cham: Springer. 2018. p. 119-129. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-319-97785-0_12

Author

Mensi, Antonelli ; Bicego, Manuele ; Lovato, Pietro ; Loog, Marco ; Tax, David M.J. / Protein remote homology detection using dissimilarity-based multiple instance learning. Structural, Syntactic, and Statistical Pattern Recognition : Joint IAPR International Workshop, S+SSPR 2018, Proceedings. editor / X. Bai ; E.R. Hancock ; T.K. Ho ; R.C. Wilson ; B. Biggio ; A. Robles-Kelly. Cham : Springer, 2018. pp. 119-129 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

BibTeX

@inproceedings{a3d844d728ce47d78fd21888a15248d2,
title = "Protein remote homology detection using dissimilarity-based multiple instance learning",
abstract = "A challenging Pattern Recognition problem in Bioinformatics concerns the detection of a functional relation between two proteins even when they show very low sequence similarity – this is the so-called Protein Remote Homology Detection (PRHD) problem. In this paper we propose a novel approach to PRHD, which casts the problem into a Multiple Instance Learning (MIL) framework, which seems very suitable for this context. Experiments on a standard benchmark show very competitive performances, also in comparison with alternative discriminative methods.",
keywords = "Multiple instance learning, N-grams, Protein homology",
author = "Antonelli Mensi and Manuele Bicego and Pietro Lovato and Marco Loog and Tax, {David M.J.}",
year = "2018",
doi = "10.1007/978-3-319-97785-0_12",
language = "English",
isbn = "978-3-319-97784-3",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer",
pages = "119--129",
editor = "X. Bai and Hancock, {E.R. } and T.K. Ho and Wilson, {R.C. } and Biggio, {B. } and Robles-Kelly, {A. }",
booktitle = "Structural, Syntactic, and Statistical Pattern Recognition",

}

RIS

TY - GEN

T1 - Protein remote homology detection using dissimilarity-based multiple instance learning

AU - Mensi, Antonelli

AU - Bicego, Manuele

AU - Lovato, Pietro

AU - Loog, Marco

AU - Tax, David M.J.

PY - 2018

Y1 - 2018

N2 - A challenging Pattern Recognition problem in Bioinformatics concerns the detection of a functional relation between two proteins even when they show very low sequence similarity – this is the so-called Protein Remote Homology Detection (PRHD) problem. In this paper we propose a novel approach to PRHD, which casts the problem into a Multiple Instance Learning (MIL) framework, which seems very suitable for this context. Experiments on a standard benchmark show very competitive performances, also in comparison with alternative discriminative methods.

AB - A challenging Pattern Recognition problem in Bioinformatics concerns the detection of a functional relation between two proteins even when they show very low sequence similarity – this is the so-called Protein Remote Homology Detection (PRHD) problem. In this paper we propose a novel approach to PRHD, which casts the problem into a Multiple Instance Learning (MIL) framework, which seems very suitable for this context. Experiments on a standard benchmark show very competitive performances, also in comparison with alternative discriminative methods.

KW - Multiple instance learning

KW - N-grams

KW - Protein homology

UR - http://www.scopus.com/inward/record.url?scp=85052216699&partnerID=8YFLogxK

U2 - 10.1007/978-3-319-97785-0_12

DO - 10.1007/978-3-319-97785-0_12

M3 - Conference contribution

SN - 978-3-319-97784-3

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 119

EP - 129

BT - Structural, Syntactic, and Statistical Pattern Recognition

A2 - Bai, X.

A2 - Hancock, E.R.

A2 - Ho, T.K.

A2 - Wilson, R.C.

A2 - Biggio, B.

A2 - Robles-Kelly, A.

PB - Springer

CY - Cham

ER -

ID: 47578862