Name
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. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1007/978-3-319-97785-0_12 | Lecture Notes in Computer Science |
Keywords | DocType | Volume |
Protein homology,N-grams,Multiple instance learning | Conference | 11004 |
ISSN | Citations | PageRank |
0302-9743 | 0 | 0.34 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Antonelli Mensi | 1 | 0 | 0.34 |
| Manuele Bicego | 2 | 1028 | 72.30 |
| Pietro Lovato | 3 | 126 | 9.80 |
| Marco Loog | 4 | 1796 | 154.31 |
| David M. J. Tax | 5 | 2071 | 148.87 |