Authors:
Leandro M. Ferreira
1
;
Cristiano L. N. Pinto
2
;
Sérgio M. Dias
3
;
Cristiane N. Nobre
1
and
Luis E. Zárate
4
Affiliations:
1
Pontifical Catholic University of Minas Gerais (PUC Minas), Brazil
;
2
UNA University Center and School of Engeneering of Minas Gerais, Brazil
;
3
Pontifical Catholic University of Minas Gerais (PUC Minas) and Federal Service of Data Processing, Brazil
;
4
UNA University Center and Pontifical Catholic University of Minas Gerais (PUC Minas), Brazil
Keyword(s):
Data Mining, Bioinformatics, Formal Concept Analysis, Machine Learning, Translation Initiation Site.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Data Mining
;
Databases and Information Systems Integration
;
Enterprise Information Systems
;
Sensor Networks
;
Signal Processing
;
Soft Computing
Abstract:
The search for conservative features that define the translation and transcription processes used by cells to interpret and express their genetic information is one of the great challenges in the molecular biology. Each transcribed mRNA sequence has only one part translated into proteins, called \textit{Coding Sequence}. The detection of this region is what motivates the search for conservative characteristics in an mRNA sequence. In eukaryotes, this region usually begins with the first occurrence of the sequence of 3 nucleotides, being Adenine, Thymine and Guanine, the nucleotide set that it is called Translation Initiation Site. One way to look for conservative rules that define this region is to use the formal analysis of concepts that can have implications that indicate a coexistence between the positions of the sequence with the presence of the translation start site. This papers tries to study the use of this technique to extract conservative rules in order to predict the trans
lation initiation site.
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