title: A Scientific Software Product Line for the Bioinformatics domain.
abstract: BACKGROUND
  Most specialized users (scientists) that use bioinformatics applications do not have suitable training on software development. Software Product Line (SPL) employs the concept of reuse considering that it is defined as a set of systems that are developed from a common set of base artifacts. In some contexts, such as in bioinformatics applications, it is advantageous to develop a collection of related software products, using SPL approach. If software products are similar enough, there is the possibility of predicting their commonalities, differences and then reuse these common features to support the development of new applications in the bioinformatics area.
  
  
  OBJECTIVE
  This paper presents the PL-Science approach which considers the context of SPL and ontology in order to assist scientists to define a scientific experiment, and to specify a workflow that encompasses bioinformatics applications of a given experiment. This paper also focuses on the use of ontologies to enable the use of Software Product Line in biological domains.
  
  
  METHODS
  In the context of this paper, Scientific Software Product Line (SSPL) differs from the Software Product Line due to the fact that SSPL uses an abstract scientific workflow model. This workflow is defined according to a scientific domain and using this abstract workflow model the products (scientific applications/algorithms) are instantiated.
  
  
  RESULTS
  Through the use of ontology as a knowledge representation model, we can provide domain restrictions as well as add semantic aspects in order to facilitate the selection and organization of bioinformatics workflows in a Scientific Software Product Line. The use of ontologies enables not only the expression of formal restrictions but also the inferences on these restrictions, considering that a scientific domain needs a formal specification.
  
  
  CONCLUSIONS
  This paper presents the development of the PL-Science approach, encompassing a methodology and an infrastructure, and also presents an approach evaluation. This evaluation presents case studies in bioinformatics, which were conducted in two renowned research institutions in Brazil.
authors.affiliation: Federal University of Juiz de Fora - Computer Science Program, Juiz de Fora, Brazil. Electronic address: gabriellabc@gmail.com.
authors.forename: Gabriella Castro B
authors.initials: GC
authors.lastname: Costa
authors.affiliation: Federal University of Juiz de Fora - Computer Science Program, Juiz de Fora, Brazil. Electronic address: regina.braga@ufjf.edu.br.
authors.forename: Regina
authors.initials: R
authors.lastname: Braga
authors.affiliation: Federal University of Juiz de Fora - Computer Science Program, Juiz de Fora, Brazil. Electronic address: jose.david@ufjf.edu.br.
authors.forename: José Maria N
authors.initials: JM
authors.lastname: David
authors.affiliation: Federal University of Juiz de Fora - Computer Science Program, Juiz de Fora, Brazil. Electronic address: fernanda.campos@ufjf.edu.br.
authors.forename: Fernanda
authors.initials: F
authors.lastname: Campos
mesh_terms: D000465:Algorithms; D001938:Brazil; D000067917:Cloud Computing; D016000:Cluster Analysis; D019295:Computational Biology / Q000295:instrumentation* / Q000379:methods*; D016208:Databases, Factual; D020407:Internet; D015588:Observer Variation; D011381:Programming Languages; D016415:Sequence Alignment; D017422:Sequence Analysis, DNA; D012984:Software
keywords: Feature model; Ontology; Scientific workflow; Sequence alignment; Software Product Line