Automated enzyme classification by formal concept analysis

TY - GEN

T1 - Automated enzyme classification by formal concept analysis

AU - Coste, François

AU - Garet, Gaëlle

AU - Groisillier, Agnès

AU - Nicolas, Jacques

AU - Tonon, Thierry

PY - 2014/1/1

Y1 - 2014/1/1

N2 - Enzymes are macro-molecules (linear sequences of linked molecules) with a catalytic activity that make them essential for any biochemical reaction. High throughput genomic techniques give access to the sequence of new enzymes found in living organisms. Guessing the enzyme's functional activity from its sequence is a crucial task that can be approached by comparing the new sequences with those of already known enzymes labeled by a family class. This task is difficult because the activity is based on a combination of small sequence patterns and sequences greatly evolved over time. This paper presents a classifier based on the identification of common subsequence blocks between known and new enzymes and the search of formal concepts built on the cross product of blocks and sequences for each class. Since new enzyme families may emerge, it is important to propose a first classification of enzymes that cannot be assigned to a known family. FCA offers a nice framework to set the task as an optimization problem on the set of concepts. The classifier has been tested with success on a particular set of enzymes present in a large variety of species, the haloacid dehalogenase superfamily.

AB - Enzymes are macro-molecules (linear sequences of linked molecules) with a catalytic activity that make them essential for any biochemical reaction. High throughput genomic techniques give access to the sequence of new enzymes found in living organisms. Guessing the enzyme's functional activity from its sequence is a crucial task that can be approached by comparing the new sequences with those of already known enzymes labeled by a family class. This task is difficult because the activity is based on a combination of small sequence patterns and sequences greatly evolved over time. This paper presents a classifier based on the identification of common subsequence blocks between known and new enzymes and the search of formal concepts built on the cross product of blocks and sequences for each class. Since new enzyme families may emerge, it is important to propose a first classification of enzymes that cannot be assigned to a known family. FCA offers a nice framework to set the task as an optimization problem on the set of concepts. The classifier has been tested with success on a particular set of enzymes present in a large variety of species, the haloacid dehalogenase superfamily.

KW - bioinformatics

KW - FCA application

KW - protein classification

UR - http://www.scopus.com/inward/record.url?scp=84903647620&partnerID=8YFLogxK

U2 - 10.1007/978-3-319-07248-7_17

DO - 10.1007/978-3-319-07248-7_17

M3 - Conference contribution

AN - SCOPUS:84903647620

SN - 9783319072470

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 235

EP - 250

BT - Formal Concept Analysis - 12th International Conference, ICFCA 2014, Proceedings

PB - Springer

T2 - 12th International Conference on Formal Concept Analysis, ICFCA 2014

Y2 - 10 June 2014 through 13 June 2014

ER -