Skip to main content

Table 2 Experimental results based on VLDB GRU algorithm

From: Research on RNA secondary structure predicting via bidirectional recurrent neural network

Dataset

Method

SEN

PPV

ACC

MCC

SPR

GRU

0.777

0.687

0.707

0.421

FLAG

0.965

0.853

0.905

0.816

VLDB

0.962

0.885

0.921

0.845

ASE

GRU

0.983

0.482

0.556

0.323

FLAG

0.806

0.532

0.645

0.36

VLDB

0.826

0.652

0.727

0.475

RFA

GRU

0.971

0.563

0.661

0.451

FLAG

0.793

0.613

0.732

0.473

VLDB

0.811

0.699

0.778

0.558

SRP

GRU

0.768

0.676

0.708

0.421

FLAG

0.798

0.653

0.697

0.408

VLDB

0.828

0.828

0.729

0.463

TMR

GRU

0.974

0.498

0.63

0.434

FLAG

0.819

0.668

0.769

0.543

VLDB

0.796

0.669

0.765

0.529

  1. The data in bold, italics, underline represent the optimal evaluation index values obtained by different algorithms on the same data set
Back to article page

BMC Bioinformatics

ISSN: 1471-2105

Contact us