Bioinformatics

2018 ◽  
pp. 26-47 ◽  
Author(s):  
Kijpokin Kasemsap
Keyword(s):  
Interdisciplinary Research ◽  
Research Area ◽  
Product Line ◽  
Biological Data ◽  
Biological Information ◽  
Clinical Bioinformatics ◽  
Software Product ◽  
Fundamental Biology ◽  
Insight Into ◽  
Chemical Cross Linking

This chapter describes the overview of bioinformatics; bioinformatics, data mining, and data visualization; bioinformatics and secretome analysis; bioinformatics, mass spectrometry, and chemical cross-linking reagents; bioinformatics and Software Product Line (SPL); bioinformatics and protein kinase; bioinformatics and MicroRNAs (miRNAs); and clinical bioinformatics and cancer. Bioinformatics is the application of computer technology to the management and analysis of biological data. Bioinformatics is an interdisciplinary research area that is the interface between biology and computer science. The primary goal of bioinformatics is to reveal the wealth of biological information hidden in the large amounts of data and obtain a clearer insight into the fundamental biology of organisms. Bioinformatics entails the creation and advancement of databases, algorithms, computational and statistical techniques, and theory to solve the formal and practical problems arising from the management and analysis of biological data.

Hybrid Model using Firefly and BBO for Feature Selection in Software Product Line

2020 ◽  
Vol 13 ◽  
Author(s):  
Hitesh Yadav ◽  
Rita Chhikara ◽  
Charan Kumari
Keyword(s):  
Hybrid Model ◽  
High Performance ◽  
Software Product Line ◽  
Product Line ◽  
Feature Model ◽  
Software Systems ◽  
Feature Sets ◽  
Research Article ◽  
Software Product ◽  
Multiple Variants

Background: Software Product Line is the group of multiple software systems which share the similar set of features with multiple variants. Feature model is used to capture and organize features used in different multiple organization. Objective: The objective of this research article is to obtain an optimized subset of features which are capable of providing high performance. Methods: In order to achieve the desired objective, two methods have been proposed. a) An improved objective function which is used to compute the contribution of each feature with weight based methodology. b) A hybrid model is employed to optimize the Software Product Line problem. Results: Feature sets varying in size from 100 to 1000 have been used to compute the performance of the Software Product Line. Conclusion: The results shows that proposed hybrid model outperforms the state of art metaheuristic algorithms.

Servant Leadership: A systematic literature review—toward a model of antecedents and outcomes

2019 ◽  
Vol 34 (1) ◽  
pp. 32-68 ◽  
Author(s):  
Jan G Langhof ◽  
Stefan Güldenberg
Keyword(s):  
Literature Review ◽  
Servant Leadership ◽  
Systematic Literature Review ◽  
Research Area ◽  
Leadership Model ◽  
Management Literature ◽  
Insight Into

The purpose of this article is multi-layered. First, we focus on gaining a comprehensive insight into a research area which just recently received more recognition in management literature: servant leadership. Second, we identify antecedent and outcomes of servant leadership within the existing research body. Third, we synthesize and develop a comprehensive servant leadership model. It assists academics and practitioners in keeping pace with the increasing servant leadership literature. The systematic literature review provides explanations as to why managers practice servant leadership. The study also contributes to a better understanding of the outcomes of servant leadership and brings clarity to a discombobulated group of studies.

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