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Pixel classification of mixed pixels in overlapping regions of remote sensing images is a very challenging task. Efficiency and detection of uncertainty are always the key ingredients for this task. This paper proposes an approach for pixel classification using Shannon's entropy-based fuzzy distance norm. Unsupervised clustering is used to group the objects based on some similarity or dissimilarit
Identification of cancer pathways is the central goal in the cancer gene expression data analysis. Data mining refers to the process analyzing huge data in order to find useful pattern. Data classification is the process of identifying common properties among a set of objects and grouping them into different classes. A cellular automaton is a discrete, dynamical system with simple uniformly interc
Pixel classification among overlapping land cover regions in remote sensing imagery is a challenging task. Detection of uncertainty and vagueness are always key features for classifying mixed pixels. This chapter proposes an approach for pixel classification using hybrid approach of Fuzzy C-Means and Particle Swarm Optimization methods. This new unsupervised algorithm is able to identify clusters
In rhizosphere Plant Growth Promoting Rhizobacteria (PGPR) produce N-acyl-l-homoserine lactones (AHL) as the quorum-sensing (QS) signals. AHLs can act as trans-kingdom signalling molecules between plants and rhizobacteria and that can regulate plant growth and development. The plant-beneficial PGPR Burkholderia phytofirmans PsJN promotes growth in Arabidopsis thaliana by producing 3-oxo-dodecanoyl
The inference of gene networks from gene expression data is known as "reverse engineering." Elucidating genetic networks from high-throughput microarray data in seed maturation and embryo formation in plants is crucial for storage and production of cereals for human beings. Delayed seed maturation and abnormal embryo formation during storage of cereal crops degrade the quality and quantity of food
A hybrid unsupervised learning algorithm, which is termed as Evolutionary Rough Multi-Objective Optimization (ERMOO) algorithm, is proposed in this chapter. It comprises a judicious integration of the principles of the rough sets theory with the archived multi-objective simulated annealing approach. While the concept of boundary approximations of rough sets in this implementation deals with the in
Background: The industrially important yeast Blastobotrys (Arxula) adeninivorans is an asexual hemiascomycete phylogenetically very distant from Saccharomyces cerevisiae. Its unusual metabolic flexibility allows it to use a wide range of carbon and nitrogen sources, while being thermotolerant, xerotolerant and osmotolerant. Results: The sequencing of strain LS3 revealed that the nuclear genome of
Identification of cancer subtypes is the central goal in the cancer gene expression data analysis. Modified symmetry-based clustering is an unsupervised learning technique for detecting symmetrical convex or non-convex shaped clusters. To enable fast automatic clustering of cancer tissues (samples), in this chapter, the authors propose a rough set based hybrid approach for modified symmetry-based
The paper discusses a life cycle model of wood products of Dalbergia sissoo from Saharanpur and Bijnor to calculate and trace the amount of carbon retained. A simulation model is built to trace the fate of carbon bound in the products produced in the year 2009 for a period of 200 years, until most of the carbon is released back into the atmosphere. The amount of carbon that enters the life cycle i
Remote homology detection among proteins utilizing only the unlabelled sequences is a central problem in comparative genomics. The existing cluster kernel methods based on neighborhoods and profiles and the Markov clustering algorithms are currently the most popular methods for protein family recognition. The deviation from random walks with inflation or dependency on hard threshold in similarity
In this paper we propose an automatic protein family expansion approach for recruitment of new members among the protein-coding genes in newly sequenced genomes. The criteria for adding a new member to a family depends on the structure of each individual family versus being globally uniform. The detection of a threshold in the ROC space of all sorted iterative profile sets defines the alignments s
Polyploidization is an important process in the evolution of eukaryotic genomes, but ensuing molecular mechanisms remain to be clarified. Autopolyploidization or whole-genome duplication events frequently are resolved in resulting lineages by the loss of single genes from most duplicated pairs, causing transient gene dosage imbalance and accelerating speciation through meiotic infertility. Allopol
We will discuss the evolution of star clusters with a large initial binary fraction, up to 95%. The initial binary population is chosen to follow the invariant orbital-parameter distributions suggested by Kroupa (1995). The Monte Carlo MOCCA simulations of star cluster evolution are compared to the observations of Milone et al. (2012) for photometric binaries. It is demonstrated that the observed
The human pathogen Enterococcus faecalis can degrade the N-linked glycans of human RNase B to acquire nutrients, but no gene or protein has been associated with this activity. We identified an 88-kDa secreted protein, endoglycosidase (Endo) E, which is most likely responsible for this activity. EndoE, encoded by ndoE, consists of an α-domain with a family 18 glycosyl hydrolase motif and a β-domain
Immunoglobulins (Igs, antibodies) are key players in adaptive immunity, and pathways mediated through the effector Fc portion of Ig are instrumental in controlling bacterial infections. Therefore, it is not very surprising that bacterial pathogens and commensals through co-evolution with their hosts have learned many tricks to interfere with Fc effector functions. In this chapter, we describe thre
Staphylococcus aureus is the causative agent of several serious infectious diseases. The emergence of antibiotic-resistant S. aureus strains has resulted in significant treatment difficulties, intensifying the need for new antimicrobial agents. Toward this end, we have developed a novel chimeric bacteriophage (phage) lysin that is active against staphylococci, including methicillin-resistant S. au
För att bättre kunna förebygga att skelettet bryts ner vid långvarig vila eller vid sjukdomarsom osteopenia och osteoporos, behövs bättre förståelse för de processer somstyr detta. I den här avhandlingen antas att den primära orsaken till bentillväxt är enförändring i den kemiska miljön i benet. Förändringen antas orsakas av att tillväxtstimulerandeämnen transporteras genom benet till den plats däIn order to prevent or modify bone degeneration due to rest or due to diseases such as osteopenia and osteoporosis, the modeling and remodeling of bone tissue must be better understood. In this thesis it is assumed that the primary condition leading to bone growth is a change of the chemical environment caused by transport of matter resulting from stress driven diffusion. The change in the chemica
