Skip to main content

Table 1 Overview of detection performance for several methods.

From: Word correlation matrices for protein sequence analysis and remote homology detection

Method

avg. ROC

avg. ROC50

avg. mRFP

avg. # SV

WCM 1

0.8705

0.3153

0.1065

1798

WCM 2

0.8926

0.3814

0.0833

1673

WCM 3

0.8964

0.4040

0.0813

1628

WCM 4

0.9013

0.4257

0.0801

1604

WCM 5

0.9032

0.4413

0.0795

1591

WCM 6

0.9044

0.4473

0.0778

1591

WCM 7

0.9036

0.4454

0.0785

1600

WCM 8

0.9024

0.4470

0.0801

1607

WCM 9

0.9018

0.4516

0.0815

1614

WCM 10

0.9012

0.4528

0.0830

1620

LA-eig

0.9348

0.6614

0.0489

2640

ODH Monomer

0.9135

0.4554

0.0729

1601

SVM pairwise

0.9008

0.3986

0.0810

2355

Mismatch (5,1)

0.8852

0.3815

0.0949

2943

Spectrum (3)

0.8239

0.2939

0.1535

2350

Spectrum {1,2}

0.8919

0.3913

0.0798

1560

Spectrum {1,2,3}

0.8957

0.4094

0.0766

1711

Spectrum {1,2,3,4}

0.8981

0.4180

0.0769

1882

  1. Performance evaluation results of the word correlation approach (WCM K ) using several word lengths K = 1, ..10 in comparison to local alignment kernel (LA-eig) [10], Monomer Distance Histograms (ODH Monomer) [14], SVM pairwise [6], Mismatch string kernel [8], Spectrum kernel [9] and the combination of Spectrum kernels for different word lengths (see section "Results").