Table 3: Tool performance comparisons.

 

Category

Tool\Metric

TPR

PPV

F-measure

MCC

Single sequence methods

Our algorithms

SSD-liberal

0.754

0.847

0.798

0.799

SSD-opt

0.662

0.811

0.729

0.732

nbRSSP-extractor

0.558

0.441

0.493

0.496

RNALfold-lnrz

0.461

0.473

0.467

0.467

MFE-based

M fold

0.52

0.541

0.53

0.531

RNA fold

0.48

0.468

0.474

0.474

Fold

0.658

0.594

0.624

0.625

ML-based

Context Fold

0.780

0.787

0.784

0.784

MEA-based

IPknot

0.580

0.676

0.624

0.626

Centroid Fold

0.550

0.717

0.622

0.628

S fold

0.503

0.508

0.505

0.505

Fold then align

MXScarna

0.610

0.725

0.663

0.665

Comparative approaches

MARNA

0.506

0.729

0.597

0.608

Align then fold

CentroidAlifold

0.650

0.867

0.743

0.751

RNAalifold

0.707

0.781

0.742

0.743

P fold

0.400

0.810

0.536

0.569

Fold and align
simultaneously

Dyn align

0.719

0.844

0.776

0.779

Fold align

0.615

0.293

0.397

0.425

Carnac

0.571

0.871

0.69

0.705

Base pairing probability

Turbo Fold

0.790

0.747

0.768

0.768

RNA sampler

0.692

0.904

0.784

0.791

 

Metrics over different RNA datasets (e.g., RNA strand, LSU, RNAse p and SM-A05), TPR = True Averaged rRNA, SSU, LGW17 positive rate; PPV = Positive Predictive Value; F-Measure, ;

MFE = Minimum Free Energy; MEA = Maximum Speed Accuracy; ML = Machine Learning.