Literature DB >> 18192302

ROC analysis: applications to the classification of biological sequences and 3D structures.

Paolo Sonego1, András Kocsor, Sándor Pongor.   

Abstract

ROC ('receiver operator characteristics') analysis is a visual as well as numerical method used for assessing the performance of classification algorithms, such as those used for predicting structures and functions from sequence data. This review summarizes the fundamental concepts of ROC analysis and the interpretation of results using examples of sequence and structure comparison. We overview the available programs and provide evaluation guidelines for genomic/proteomic data, with particular regard to applications to large and heterogeneous databases used in bioinformatics.

Mesh:

Year:  2008        PMID: 18192302     DOI: 10.1093/bib/bbm064

Source DB:  PubMed          Journal:  Brief Bioinform        ISSN: 1467-5463            Impact factor:   11.622


  49 in total

1.  Evaluation of a hypothetical protein for serodiagnosis and as a potential marker for post-treatment serological evaluation of tegumentary leishmaniasis patients.

Authors:  Mariana Pedrosa Lima; Lourena Emanuele Costa; Mariana Costa Duarte; Daniel Menezes-Souza; Beatriz Cristina Silveira Salles; Thaís Teodoro de Oliveira Santos; Fernanda Fonseca Ramos; Miguel Angel Chávez-Fumagalli; Amanda Christine Silva Kursancew; Roberta Passamani Ambrósio; Bruno Mendes Roatt; Ricardo Andrez Machado-de-Ávila; Denise Utsch Gonçalves; Eduardo Antonio Ferraz Coelho
Journal:  Parasitol Res       Date:  2017-02-01       Impact factor: 2.289

2.  Spatial analysis of magnetic resonance T1rho and T2 relaxation times improves classification between subjects with and without osteoarthritis.

Authors:  Julio Carballido-Gamio; Robert Stahl; Gabrielle Blumenkrantz; Adan Romero; Sharmila Majumdar; Thomas M Link
Journal:  Med Phys       Date:  2009-09       Impact factor: 4.071

3.  SIMON, an Automated Machine Learning System, Reveals Immune Signatures of Influenza Vaccine Responses.

Authors:  Adriana Tomic; Ivan Tomic; Yael Rosenberg-Hasson; Cornelia L Dekker; Holden T Maecker; Mark M Davis
Journal:  J Immunol       Date:  2019-06-14       Impact factor: 5.422

4.  Computer-Assisted Diagnosis System for Breast Cancer in Computed Tomography Laser Mammography (CTLM).

Authors:  Afsaneh Jalalian; Syamsiah Mashohor; Rozi Mahmud; Babak Karasfi; M Iqbal Saripan; Abdul Rahman Ramli
Journal:  J Digit Imaging       Date:  2017-12       Impact factor: 4.056

5.  Detecting causality in policy diffusion processes.

Authors:  Carsten Grabow; James Macinko; Diana Silver; Maurizio Porfiri
Journal:  Chaos       Date:  2016-08       Impact factor: 3.642

6.  Forest fire risk assessment-an integrated approach based on multicriteria evaluation.

Authors:  Elham Goleiji; Seyed Mohsen Hosseini; Nematollah Khorasani; Seyed Masoud Monavari
Journal:  Environ Monit Assess       Date:  2017-11-06       Impact factor: 2.513

7.  Recognition of beta-structural motifs using hidden Markov models trained with simulated evolution.

Authors:  Anoop Kumar; Lenore Cowen
Journal:  Bioinformatics       Date:  2010-06-15       Impact factor: 6.937

8.  Augmented training of hidden Markov models to recognize remote homologs via simulated evolution.

Authors:  Anoop Kumar; Lenore Cowen
Journal:  Bioinformatics       Date:  2009-04-23       Impact factor: 6.937

9.  Predicting beta-turns and their types using predicted backbone dihedral angles and secondary structures.

Authors:  Petros Kountouris; Jonathan D Hirst
Journal:  BMC Bioinformatics       Date:  2010-07-31       Impact factor: 3.169

10.  Ab-origin: an enhanced tool to identify the sourcing gene segments in germline for rearranged antibodies.

Authors:  Xiaojing Wang; Di Wu; Siyuan Zheng; Jing Sun; Lin Tao; Yixue Li; Zhiwei Cao
Journal:  BMC Bioinformatics       Date:  2008-12-12       Impact factor: 3.169

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