Literature DB >> 16226240

Machine learning in bioinformatics: a brief survey and recommendations for practitioners.

Harish Bhaskar1, David C Hoyle, Sameer Singh.   

Abstract

Machine learning is used in a large number of bioinformatics applications and studies. The application of machine learning techniques in other areas such as pattern recognition has resulted in accumulated experience as to correct and principled approaches for their use. The aim of this paper is to give an account of issues affecting the application of machine learning tools, focusing primarily on general aspects of feature and model parameter selection, rather than any single specific algorithm. These aspects are discussed in the context of published bioinformatics studies in leading journals over the last 5 years. We assess to what degree the experience gained by the pattern recognition research community pervades these bioinformatics studies. We finally discuss various critical issues relating to bioinformatic data sets and make a number of recommendations on the proper use of machine learning techniques for bioinformatics research based upon previously published research on machine learning.

Mesh:

Year:  2005        PMID: 16226240     DOI: 10.1016/j.compbiomed.2005.09.002

Source DB:  PubMed          Journal:  Comput Biol Med        ISSN: 0010-4825            Impact factor:   4.589


  21 in total

1.  Comparative Chemometric Analysis for Classification of Acids and Bases via a Colorimetric Sensor Array.

Authors:  Michael J Kangas; Raychelle M Burks; Jordyn Atwater; Rachel M Lukowicz; Billy Garver; Andrea E Holmes
Journal:  J Chemom       Date:  2017-10-13       Impact factor: 2.467

2.  Reconstruct modular phenotype-specific gene networks by knowledge-driven matrix factorization.

Authors:  Xuerui Yang; Yang Zhou; Rong Jin; Christina Chan
Journal:  Bioinformatics       Date:  2009-06-19       Impact factor: 6.937

3.  Biomarker panels in ischemic stroke.

Authors:  Glen C Jickling; Frank R Sharp
Journal:  Stroke       Date:  2015-02-05       Impact factor: 7.914

4.  The potential for leveraging machine learning to filter medication alerts.

Authors:  Siru Liu; Kensaku Kawamoto; Guilherme Del Fiol; Charlene Weir; Daniel C Malone; Thomas J Reese; Keaton Morgan; David ElHalta; Samir Abdelrahman
Journal:  J Am Med Inform Assoc       Date:  2022-04-13       Impact factor: 4.497

5.  Data-driven advice for applying machine learning to bioinformatics problems.

Authors:  Randal S Olson; William La Cava; Zairah Mustahsan; Akshay Varik; Jason H Moore
Journal:  Pac Symp Biocomput       Date:  2018

6.  Protein sequences classification by means of feature extraction with substitution matrices.

Authors:  Rabie Saidi; Mondher Maddouri; Engelbert Mephu Nguifo
Journal:  BMC Bioinformatics       Date:  2010-04-08       Impact factor: 3.169

7.  Predicting RNA-binding residues from evolutionary information and sequence conservation.

Authors:  Yu-Feng Huang; Li-Yuan Chiu; Chun-Chin Huang; Chien-Kang Huang
Journal:  BMC Genomics       Date:  2010-12-02       Impact factor: 3.969

8.  DNA-binding residues and binding mode prediction with binding-mechanism concerned models.

Authors:  Yu-Feng Huang; Chun-Chin Huang; Yu-Cheng Liu; Yen-Jen Oyang; Chien-Kang Huang
Journal:  BMC Genomics       Date:  2009-12-03       Impact factor: 3.969

9.  Elucidation of functional consequences of signalling pathway interactions.

Authors:  Adaoha E C Ihekwaba; Phuong T Nguyen; Corrado Priami
Journal:  BMC Bioinformatics       Date:  2009-11-06       Impact factor: 3.169

10.  Detecting evolution of bioinformatics with a content and co-authorship analysis.

Authors:  Christopher C Yang; Min Song; Xuning Tang
Journal:  Springerplus       Date:  2013-04-26
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.