Vol. 5, No. 2 February 2014 ISSN 2079-8407 Journal of Emerging Trends in Computing and Information Sciences ©2009-2014 CIS Journal. All rights reserved. http://www.cisjournal.org 80 Motivation and Justification of Naturalistic Method for Bioinformatics Research 1 Nooruldeen Nasih Qader, 2 Hussein Keitan Al-Khafaji 1 Computer Science, University of Sulaimani, Sulaimani, Iraq 2 Computer Communication, Alrafidain University College, Baghdad, Iraq ABSTRACT This paper introduces and proposes naturalistic method as a trends base for the Bioinformatics research. Naturalistic method emphasizes on finding biodata properties by insight in a real data nature to reflect its de facto and to be as far from the Bioinformatics theoretical assumptions as possible. We present and justify motivating factors in this direction such as studies that depend mainly on hypotheses models lead to the derivation of imperfect biological models, availability of huge real data, furthermore new technologies enable sustainable flow of data. This method aims to find better ways for representing biological data and process. This goal could be reached by finding biodata properties and characteristics. On the other hand, discovered properties could be utilized to enhance different algorithm in Bioinformatics. Keywords: Naturalistic, Bioinformatics, microarray, property, algorithm, data mining, motif, genome, gene, PWM, nucleotide, DNA, binding site. 1. INTRODUCTION The research methodologies are continuously developing to involve new techniques and ideas. Therefore, the appearance of the network and the web made it possible for the scientific community to share data produced by high throughput techniques, thus providing massive, new and free data to be investigated and analyzed. A set of data on its own is very hard to interpret. There is a lot of information contained in the data, but it is hard to see. Ways of understanding important features of the data are necessary [1], [2]. In this study we demonstrated shortcoming and disadvantages of using theoretical assumptions in Bioinformatics such as in motif representation and sequence generation. Also, we briefly introduced naturalistic method. The aim of this work is basically to present motivation and justification factors to shift Bioinformatics research to rely more on available data. To overcome challenges faced in researches, different disciplines continuously conduct the process of designing new methods beside ordinary research methods; pragmatism was a philosophical foundation for new methods of research [3], [4]. In this context disciplines such as Bioinformatics and more precisely data mining in Bioinformatics come in advance. These efforts lead to good progress, knowledge and efficiency in medicine and Bioinformatics. In Bioinformatics, recent trends concentrate on the nature of biological data to make a design more efficient [5]. The situation results in an increase in the amount of information mining from the data. This study proposes and emphasis on naturalistic and realistic trend as a base for the Bioinformatics research method. 2. RELATED WORK No single scientific method could be applied to all branches of science. Pragmatism and finding solution to a problem made scientists use whatever they can. In the following we present some related ideas to researches methods: 2.1 Deduction Philosophy vs. Induction Philosophy In the article called “Is the Scientific Paper a Fraud?” Peter Medewar reported in which induction, unlike with deductions, acquired no place with scientific research. Medewar agrees with Karl Popper, a philosopher of science. Popper refused induction being a legit sort of judgment from the process of scientific research [6]. The reason why in which deductions generally seems to delight in recommended philosophical standing subsequently is if typically the axiom plus the observation are generally appropriate typically the logical inference needs to be appropriate. By contrast, induction sometimes appears is noted as being not secure philosophically simply because it collapses to help counter-examples [7]. 2.2 Hypothesis-driven and Data-driven Method Popper and Medewar argued vehemently for a method of scientific practice based on the so-called hypothetico-deductive system, the essence of which is the formulation of a hypothesis derived from a collection of facts, testing the hypothesis by trying to ‘falsify’ it,