@article{EverardoPerezOsorio2020,
  author    = {Everardo P{\´e}rez, Flavio Omar and Osorio, Mauricio},
  title     = {Towards an answer set programming methodology for constructing programs following a semi-automatic approach},
  series = {Electronic notes in theoretical computer science},
  volume    = {354},
  journal   = {Electronic notes in theoretical computer science},
  publisher = {Elsevier},
  address   = {Amsterdam [u.a.]},
  issn      = {1571-0661},
  doi       = {10.1016/j.entcs.2020.10.004},
  pages     = {29 -- 44},
  year      = {2020},
  abstract  = {Answer Set Programming (ASP) is a successful rule-based formalism for modeling and solving knowledge-intense combinatorial (optimization) problems. Despite its success in both academic and industry, open challenges like automatic source code optimization, and software engineering remains. This is because a problem encoded into an ASP might not have the desired solving performance compared to an equivalent representation. Motivated by these two challenges, this paper has three main contributions. First, we propose a developing process towards a methodology to implement ASP programs, being faithful to existing methods. Second, we present ASP encodings that serve as the basis from the developing process. Third, we demonstrate the use of ASP to reverse the standard solving process. That is, knowing answer sets in advance, and desired strong equivalent properties, "we" exhaustively reconstruct ASP programs if they exist. This paper was originally motivated by the search of propositional formulas (if they exist) that represent the semantics of a new aggregate operator. Particularly, a parity aggregate. This aggregate comes as an improvement from the already existing parity (xor) constraints from xorro, where lacks expressiveness, even though these constraints fit perfectly for reasoning modes like sampling or model counting. To this end, this extended version covers the fundaments from parity constraints as well as the xorro system. Hence, we delve a little more in the examples and the proposed methodology over parity constraints. Finally, we discuss our results by showing the only representation available, that satisfies different properties from the classical logic xor operator, which is also consistent with the semantics of parity constraints from xorro.},
  language  = {en}
}
@article{RohrmannTohgeAlbaetal.2011,
  author    = {Rohrmann, Johannes and Tohge, Takayuki and Alba, Rob and Osorio, Sonia and Caldana, Camila and McQuinn, Ryan and Arvidsson, Samuel Janne and van der Merwe, Margaretha J. and Riano-Pachon, Diego Mauricio and M{\"u}ller-R{\"o}ber, Bernd and Fei, Zhangjun and Nesi, Adriano Nunes and Giovannoni, James J. and Fernie, Alisdair R.},
  title     = {Combined transcription factor profiling, microarray analysis and metabolite profiling reveals the transcriptional control of metabolic shifts occurring during tomato fruit development},
  series = {The plant journal},
  volume    = {68},
  journal   = {The plant journal},
  number    = {6},
  publisher = {Wiley-Blackwell},
  address   = {Malden},
  issn      = {0960-7412},
  doi       = {10.1111/j.1365-313X.2011.04750.x},
  pages     = {999 -- 1013},
  year      = {2011},
  abstract  = {Maturation of fleshy fruits such as tomato (Solanum lycopersicum) is subject to tight genetic control. Here we describe the development of a quantitative real-time PCR platform that allows accurate quantification of the expression level of approximately 1000 tomato transcription factors. In addition to utilizing this novel approach, we performed cDNA microarray analysis and metabolite profiling of primary and secondary metabolites using GC-MS and LC-MS, respectively. We applied these platforms to pericarp material harvested throughout fruit development, studying both wild-type Solanum lycopersicum cv. Ailsa Craig and the hp1 mutant. This mutant is functionally deficient in the tomato homologue of the negative regulator of the light signal transduction gene DDB1 from Arabidopsis, and is furthermore characterized by dramatically increased pigment and phenolic contents. We choose this particular mutant as it had previously been shown to have dramatic alterations in the content of several important fruit metabolites but relatively little impact on other ripening phenotypes. The combined dataset was mined in order to identify metabolites that were under the control of these transcription factors, and, where possible, the respective transcriptional regulation underlying this control. The results are discussed in terms of both programmed fruit ripening and development and the transcriptional and metabolic shifts that occur in parallel during these processes.},
  language  = {en}
}