Improved particle swarm optimization and gravitational search algorithm for parameter estimation in aspartate pathways

One of the main issues in biological system is to characterize the dynamic behaviour of the complex biological processes. Usually, metabolic pathway models are used to describe the complex processes that involve many parameters. It is important to have an accurate and complete set of parameters that describe the characteristics of a given model. Therefore, the parameter values are estimated by fitting the model with experimental data. However, the estimation on these parameters is typically difficult and even impossible in some cases. Furthermore, the experimental data are often incomplete and also suffer from experimental noise. These shortcomings make it challenging to identify the best-fit parameters that can represent the actual biological processes involved in biological systems. Previously, a computational approach namely optimization algorithms are used to estimate the measurement of the model parameters. Most of these algorithms previously often suffered bad estimation for the biological system models, which resulted in bad fitting (error) the model with the experimental data. This research proposes a parameter estimation algorithm that can reduce the fitting error between the models and the experimental data. The proposed algorithm is an Improved Particle Swarm Optimization and Gravitational Search Algorithm (IPSOGSA) to obtain the near-optimal kinetic parameter values from experimental data. The improvement in this algorithm is a local search, which aims to increase the chances to obtain the global solution. The outcome of this research is that IPSOGSA can outperform other comparison algorithms in terms of root mean squared error (RMSE) and predictive residual error sum of squares (PRESS) for the estimated results. IPSOGSA manages to score the smallest RMSE with 12.2125 and 0.0304 for Ile and HSP metabolite respectively. The predicted results are benefits for the estimation of optimal kinetic parameters to improve the production of desired metabolites

Bioinformatics Applications Based On Machine Learning

The great advances in information technology (IT) have implications for many sectors, such as bioinformatics, and has considerably increased their possibilities. This book presents a collection of 11 original research papers, all of them related to the application of IT-related techniques within the bioinformatics sector: from new applications created from the adaptation and application of existing techniques to the creation of new methodologies to solve existing problems

Exploring alternative oxidase (AOX) as a functional marker candidate for efficient somatic embryogenesis in Daucus carota L.

A embriogénese somática é o mais conhecido exemplo de reprogramação celular. Daucus carota L. foi a primeira espécie onde a totipotência foi comprovada, através da embriogénese somática. No entanto, mesmo em Daucus, considerada como modelo e facilmente induzível, existe uma influência genética na capacidade das células para serem reprogramadas. Neste sentido, a identificação de marcadores para a ‘fácil reprogramação’ pode ajudar ao desenvolvimento de marcadores funcionais para a eficiente propagação in vitro de genótipos recalcitrantes. Tendo como objetivo explorar esta questão e usando a oxidase alternativa como o gene candidato a marcador funcional, 28 genótipos de Daucus foram induzidos a realizar embriogénese somática indireta. Desses, 25 responderam ao processo, produzindo 139 linhas celulares. A eficiência embriogénica das linhas foi avaliada utilizando um método de fenotipagem em dois passos, concebido para a seleção dos fenótipos estáveis. Após o primeiro passo de fenotipagem, 41 linhas com eficiência embriogénica estável foram avaliadas e caracterizadas em relação à diversidade genética utilizando o método cTBP. Destas, 22 foram selecionados para o segundo passo de fenotipagem. Finalmente, 8 linhas celulares foram identificadas, como altamente estáveis para as eficiências embriogénicas extremas. Quatro eram muito eficientes ou muito eficientes / eficientes, e as restantes não-embriogénicas. Estas foram estabelecidas como a coleção base utilizada para uma avaliação mais aprofundada, tanto em relação à ploidia, como na investigação da oxidase alternativa. Foi detectada poliploidia em três das linhas celulares, independentemente da sua capacidade embriogénica. No entanto, considerando a mais recente informação, em que se refere a poliploidia como uma importante fonte de variabilidade para a tolerância ao stress geral, a sua utilização no presente estudo foi considerada. Os três genes da oxidase alternativa foram amplificados a partir da coleção base e explorados tendo em vista a identificação de posições polimórficas associadas com os fenótipos definidos. No total, 290 sequências foram amplificadas, das quais 47 foram identificadas como polimórficas. Destas, 11 foram identificadas como oxidase alternativa 1, 22 como 2a e 14 como 2b, sendo que a maior variabilidade foi detetada no gene 2a. As análises filogenéticas realizadas, não permitiram a identificação de qualquer grupo de sequências associado a qualquer um dos fenótipos em estudo. No entanto, a procura por elementos de regulação realizada nas zonas codificantes em cada um dos genes, detetou três elementos nas sequências do gene 2b, que estavam associados maioritariamente a linhas embriogénicas. De igual forma, também os resultados do intrão 1 no gene 2b obtidos a partir do IMeter, apontam este como possível regulador das atividades do gene nessas linhas. Embora limitadas, tais observações apontam para o 2b, como sendo o gene envolvido na capacidade das células de Daucus para desenvolver embriões. No entanto, e dadas as limitações, tal indicação requer uma investigação mais aprofundada; Abstract: The somatic embryogenesis (SE) process is the most prominent example of cell reprogramming. Daucus carota L. is the first species where totipotency through SE was proven. However, even in an easily inducible plant like Daucus, the reprogramming capacity of cells is largely influenced by their genotype. In this view, the identification of markers for ‘easy-reprogramming’, is expected to help develop functional markers for efficient biotechnological propagation of recalcitrant genotypes. Aiming to explore this issue using alternative oxidase (AOX) as the functional marker gene candidate, 28 Daucus accessions were induced to perform SE. Of those, 25 were responsive, producing 139 true-to-type cell lines. SE efficiencies were evaluated throughout a two-step phenotyping method planned for the selection of stable phenotypes. After the first phenotyping step, 41 cell lines with stable SE efficiency, were further analysed and characterized concerning genetic diversity, using the cTBP method. From these, 22 were selected for the second phenotyping step. Eight cell lines were identified at the end as highly stable for extreme SE efficiencies. Four were very efficient or very efficient / efficient, and the other four were non-embryogenic. Those were established as the basic collection used for further poidy assessment and molecular analyses of AOX. Polyploidy was detected in three of the cell lines, independently of their embryogenic capacity. However, attending the recent studies reporting polyploidy as an important source of variability for general stress tolerance, it was determined to proceed including them. The three AOXs were amplified from the collection and explored in view of the identification of polymorphic positions associated with the detected SE phenotype. In total, 290 sequences were amplified, from which, 47 were identified as polymorphic. From those, 11 were identified as AOX1, 22 as 2a and 14 as 2b, being AOX2a the main source of sequence variability. General phylogenetic analysis did not allow the identification of any group of sequences associated with any SE phenotype. Nevertheless, the search for regulatory elements performed for each gene coding region, detected three elements in the AOX2b sequences which were enriched in the embryogenic lines. In the same way, also IMEter results obtained from AOX2b intron 1 sequences, reveal these as likely candidates to regulate gene activities. Such observations, point to AOX2b, as a gene involved in the capacity of the Daucus cell's to develop embryos. However, given the limited observations, further investigation is required to better substantiate this conclusion

Enhancing the bees algorithm using the traplining metaphor

This work aims to improve the performance of the Bees Algorithm (BA), particularly in terms of simplicity, accuracy, and convergence. Three improvements were made in this study as a result of bees’ traplining behaviour. The first improvement was the parameter reduction of the Bees Algorithm. This strategy recruits and assigns worker bees to exploit and explore all patches. Both searching processes are assigned using the Triangular Distribution Random Number Generator. The most promising patches have more workers and are subject to more exploitation than the less productive patches. This technique reduced the original parameters into two parameters. The results show that the Bi-BA is just as efficient as the basic BA, although it has fewer parameters. Following that, another improvement was proposed to increase the diversification performance of the Combinatorial Bees Algorithm (CBA). The technique employs a novel constructive heuristic that considers the distance and the turning angle of the bees’ flight. When foraging for honey, bees generally avoid making a sharp turn. By including this turning angle as the second consideration, it can control CBA’s initial solution diversity. Third, the CBA is strengthened to enable an intensification strategy that avoids falling into a local optima trap. The approach is based on the behaviour of bees when confronted with threats. They will keep away from re-visiting those flowers during the next bout for reasons like predators, rivals, or honey run out. The approach will remove temporarily threatened flowers from the whole tour, eliminating the sharp turn, and reintroduces them again to the habitual tour’s nearest edge. The technique could effectively achieve an equilibrium between exploration and exploitation mechanisms. The results show that the strategy is very competitive compared to other population-based nature-inspired algorithms. Finally, the enhanced Bees Algorithms are demonstrated on two real-world engineering problems, namely, Printed Circuit Board insertion sequencing and vehicles routing problem

Simulated Annealing

The book contains 15 chapters presenting recent contributions of top researchers working with Simulated Annealing (SA). Although it represents a small sample of the research activity on SA, the book will certainly serve as a valuable tool for researchers interested in getting involved in this multidisciplinary field. In fact, one of the salient features is that the book is highly multidisciplinary in terms of application areas since it assembles experts from the fields of Biology, Telecommunications, Geology, Electronics and Medicine

Using MapReduce Streaming for Distributed Life Simulation on the Cloud

Distributed software simulations are indispensable in the study of large-scale life models but often require the use of technically complex lower-level distributed computing frameworks, such as MPI. We propose to overcome the complexity challenge by applying the emerging MapReduce (MR) model to distributed life simulations and by running such simulations on the cloud. Technically, we design optimized MR streaming algorithms for discrete and continuous versions of Conway’s life according to a general MR streaming pattern. We chose life because it is simple enough as a testbed for MR’s applicability to a-life simulations and general enough to make our results applicable to various lattice-based a-life models. We implement and empirically evaluate our algorithms’ performance on Amazon’s Elastic MR cloud. Our experiments demonstrate that a single MR optimization technique called strip partitioning can reduce the execution time of continuous life simulations by 64%. To the best of our knowledge, we are the first to propose and evaluate MR streaming algorithms for lattice-based simulations. Our algorithms can serve as prototypes in the development of novel MR simulation algorithms for large-scale lattice-based a-life models.https://digitalcommons.chapman.edu/scs_books/1014/thumbnail.jp

Toward a Sustainable Agriculture Through Plant Biostimulants

Over the past decade, interest in plant biostimulants has been on the rise, compelled by the growing interest of researchers, extension specialists, private industries, and farmers in integrating these products in the array of environmentally friendly tools to secure improved crop performance, nutrient efficiency, product quality, and yield stability. Plant biostimulants include diverse organic and inorganic substances, natural compounds, and/or beneficial microorganisms such as humic acids, protein hydrolysates, seaweed and plant extracts, silicon, endophytic fungi like mycorrhizal fungi, and plant growth-promoting rhizobacteria belonging to the genera Azospirillum, Azotobacter, and Rhizobium. Other substances (e.g., chitosan and other biopolymers and inorganic compounds) can have biostimulant properties, but their classification within the group of biostimulants is still under consideration. Plant biostimulants are usually applied to high-value crops, mainly greenhouse crops, fruit trees and vines, open-field crops, flowers, and ornamentals to sustainably increase yield and product quality. The global biostimulant market is currently estimated at about $2.0 billion and is expected to reach$3.0 billion by 2021 at an annual growth rate of 13%. A growing interest in plant biostimulants from industries and scientists was demonstrated by the high number of published peer-reviewed articles, conferences, workshops, and symposia in the past ten years. This book compiles several original research articles, technology reports, methods, opinions, perspectives, and invited reviews and mini reviews dissecting the biostimulatory action of these natural compounds and substances and beneficial microorganisms on crops grown under optimal and suboptimal growing conditions (e.g., salinity, drought, nutrient deficiency and toxicity, heavy metal contaminations, waterlogging, and adverse soil pH conditions). Also included are contributions dealing with the effect as well as the molecular and physiological mechanisms of plant biostimulants on nutrient efficiency, product quality, and modulation of the microbial population both quantitatively and qualitatively. In addition, identification and understanding of the optimal method, time, rate of application and phenological stage for improving plant performance and resilience to stress as well as the best combinations of plant species/cultivar × environment × management practices are also reported. We strongly believe that high standard reflected in this compilation on the principles and practices of plant biostimulants will foster knowledge transfer among scientific communities, industries, and agronomists, and will enable a better understanding of the mode of action and application procedures of biostimulants in different cropping systems

Investigation of Volatile Organic Compounds (VOCs) released as a result of spoilage in whole broccoli, carrots, onions and potatoes with HS-SPME and GC-MS

Vegetable spoilage renders a product undesirable due to changes in sensory characteristics. The aim of this study was to investigate the change in the fingerprint of VOC composition that occur as a result of spoilage in broccoli, carrots, onions and potatoes. SPME and GC-MS techniques were used to identify and determine the relative abundance of VOC associated with both fresh and spoilt vegetables. Although a number of similar compounds were detected in varying quantities in the headspace of fresh and spoilt samples, certain compounds which were detected in the headspace of spoilt vegetables were however absent in fresh samples. Analysis of the headspace of fresh vegetables indicated the presence of a variety of alkanes, alkenes and terpenes. Among VOCs identified in the spoilt samples were dimethyl disulphide and dimethyl sulphide in broccoli; Ethyl propanoate and Butyl acetate in carrots; 1-Propanethioland 2-Hexyl-5-methyl-3(2H)-furanone in onions; and 2, 3-Butanediol in potatoes. The overall results of this study indicate the presence of VOCs that can serve as potential biomarkers for early detection of quality deterioration and in turn enhance operational and quality control decisions in the vegetable industry

2018 EURēCA Abstract Book

Listing of student participant abstracts