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12th International conference on Practical Applications of computational Biology and bioinformatics (PACBB)

作者： Sequeira, Joao Carlos Rocha, Miguel Alves, Maria Madalena Salvador, Andreia Ferreira Univ Minho Ctr Biol Engn Campus Gualtar Braga Portugal

ISBN: (纸本)9783319987026;9783319987019

Metagenomics (MG) and Metatranscriptomics (MT) approaches open new perspectives on the interpretation of biological systems composed by complexmicrobial communities. Dealing with large sequencing datasets, to extract the desired information and interpret the results are big challenges associated with meta-omics studies. There are several bioinformatics pipelines forMG data analysis and less toMT. Up to date, none performs a complete analysis integrating both MG and MT data, including the assembly of reads into contigs, functional and taxonomic annotation of identified genes, differential gene expression analysis and the comparison of multiple samples. Here, we present Meta-Omics Software for Community Analysis (MOSCA) that was designed with this purpose. It integrates RNA-Seq analysis with Whole Genome Sequencing as reference. Raw sequencing reads are submitted to preprocessing for quality trimming and rRNA removal, and assembled into contigs, which afterwards are annotated by using a reference database. MOSCA performs differential gene expression and provides graphical visualization of the results and comparison of multiple samples. Validation and reproducibility of the pipeline was obtained by using simulated MG and MT datasets.

关键词： Metagenomics Metatranscriptomics bioinformatics pipeline Community analysis RNA-Seq Whole genome sequencing

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Duck Eggs Hatching Procedure with A Low Cost User Convenient Integrated Device for Developing Countries

Duck Eggs Hatching Procedure with A Low Cost User Convenient...

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ieee Region 10 Humanitarian Technology conference (R10-HTC)

作者： Eftakhar Hossain Mohammad Zeyad S.M. Masum Ahmed Md Sadik Tasrif Anubhove Energy and Technology Research Division Advanced Bioinformatics Computational Biology and Data Science Laboratory Bangladesh Chattogram Bangladesh Erasmus+ Joint MSC in Smart Cities and Communities University of the Basque Country (UPV/EHU) Bilbao Spain

Poultry agriculture is a form of livestock farming that involves raising chickens, turkeys, ducks, etc, and raises them to provide eggs or meat. However, this work sheds light on the method of hatching duck eggs which maintains a suitable environment around the eggs through an automated and low cost device by controlling temperature (T) and relative humidity (RH). This paper presents a control strategy for automatic temperature and relative humidity control systems for the egg/s hatching procedure for rural areas people or unprivileged communities in the developing countries. One of the best outcomes of this work is the proper hatching procedure steps shown from the beginning to the end. Moreover, for a better understanding and outcomes, the research work has been done under a poultry farm in Charsita village, Lakshmipur, Bangladesh for 6 consecutive months of 2020. The experiment (egg/s hatching) has been conducted under an ice-box. Furthermore, a microcontroller (ATmega328p) is used to monitor the temperature and relative humidity by receiving data from the sensor DHT22 and manipulating the appropriate temperature and humidity using a logic algorithm code. Egg/s need a constant temperature and relative humidity of 35.6 °C to 37.8 °C and 60% to 80%, respectively. Nonetheless, an LCD (16*2) with a matrix keypad (4*4) has been integrated into the unit, allowing farmers to easily set, run, and monitor the appropriate temperature and relative humidity levels within the ice-box. Finally, the results of sensor testing, system device management, and performance rates are recorded to ensure the research's success.

关键词： Temperature sensors Temperature measurement Temperature distribution Costs Rural areas Humidity Developing countries

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Fourier Surrogate Models of Dilated Fitness Landscapes in systems Biology : or how we learned to torture optimization problems until they confess

Fourier Surrogate Models of Dilated Fitness Landscapes in Sy...

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ieee Symposium on computational Intelligence and bioinformatics and computational Biology (CIBCB)

作者： Marco S. Nobile Paolo Cazzaniga Simone Spolaor Daniela Besozzi Luca Manzoni Eindhoven University of Technology (TU/e) Eindhoven AZ The Netherlands SYSBIO/ISBE.IT Centre for Systems Biology Milano Italy University of Bergamo Bergamo Italy University of Milano-Bicocca Milano Italy Bicocca Bioinformatics Biostatistics and Bioimaging Centre (B4) Monza Italy University of Trieste Trieste Italy

ISBN: (数字)9781728194684

ISBN: (纸本)9781728194691

One of the most complex problems in systems Biology is Parameter estimation (PE), which consists in inferring the kinetic parameters of biochemical systems. The identification of an accurate parameterization, able to reproduce any observed experimental behavior, is fundamental for the definition of predictive models. PE is a non-convex, multi-modal, and non-separable problem that is usually tackled by using computational Intelligence methods. When the biochemical species appear in the system in a very low amount, the intrinsic noise due to the randomness of molecular collisions cannot be neglected. In this case, stochastic simulation algorithms should be employed to properly reproduce the system dynamics. Stochastic fluctuations make the PE problem even more complicated, as they can lead to radically different values of the fitness function for the same candidate parameterization. In addition, the kinetic parameters generally follow a log-uniform distribution, so that global optima tend to be localized in the lowest orders of magnitude of the search space. To simultaneously tackle all the aforementioned issues, in this work we investigate a novel approach based on the combination of dilation functions with Fourier surrogate modeling and filtering on the fitness landscape. The results show that our approach is able to strongly simplify the PE problem for low-dimensional optimization instances.

关键词： Stochastic processes Optimization Biological system modeling Solid modeling Semantics Mathematical model computational modeling

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Exploring computational Inference of Microbial Interactions and their Dynamics 14

Exploring Computational Inference of Microbial Interactions ...

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14th ieee International conference on Industrial and Information systems, ICIIS 2019

作者： Vidanaarachchi, Rajith Shaw, Marnie Halgamuge, Saman Research School of Electrical Energy and Materials Engineering Australian National University Australia University of Melbourne Department of Mechanical Engineering Australia

ISBN: (数字)9781728137063

ISBN: (纸本)9781728137063

Next Generation Sequencing has increased detailed studies of microbial communities. Understanding microbial interactions is crucial for understanding these communities. Microbial Interaction Networks (MINs) have been inferred using microbial abundance profiles, using multiple methods and frameworks. In this paper we explore current approaches in inferring microbial interactions and demonstrate that they are dynamic in nature, and propose a visualisation approach for observing dynamic nature of MINs. Our work highlights that even very rare microbiota have bursts of high abundance at some time points. Further, we suggest possible improvements in the field of computational inference of MINs. © 2019 ieee.

关键词： bioinformatics

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17α-Ethinylestradiol Analysis of Endo- and Exometabolome of Ulva lactuca (Chlorophyta) by ¹H-NMR Spectroscopy and bioinformatics Tools 12th

17α-Ethinylestradiol Analysis of Endo- and Exometabolome of...

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12th International conference on Practical Applications of computational Biology and bioinformatics (PACBB)

作者： Cabral, Debora Cardoso, Sara Rocco, Silvana Sforca, Mauricio Hengeltraub, Simone Fanan Bauer, Claudia Rocha, Miguel Maraschin, Marcelo Univ Fed Santa Catarina Plant Morphogenesis & Biochem Lab Florianopolis SC Brazil Univ Minho Ctr Biol Engn Braga Portugal Brazilian Biosci Natl Lab LNBio CNPEM Campinas SP Brazil

ISBN: (纸本)9783319987026;9783319987019

The uptake of 17 alpha-ethinylestradiol (EE2) by the green alga Ulva lactuca and its effects on the metabolome of that macroalgae have been investigated using H-1-NMR spectroscopy. To this end, U. lactuca in vitro cultures have been acutely (48 h) exposed to the estrogen and both, endo-and exometabolome were investigated. Bioinformatic analyses were performed to integrate and analyze endo-and exometabolic profiles allowing the detection of EE2 into exometabolome samples and identifying very important parameters (VIPs), i.e., H-1-NMR resonances, responsible for grouping similar U. lactuca metabolic profiles and biochemical phenotypes.

关键词： Ulva lactuca 17 alpha-ethinylestradiol NMR spectroscopy Endometabolome Exometabolome

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Selected Papers of the First International conference on Algorithms for computational Biology (AICoB 2014)

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ieee-ACM TRANSACTIONS ON computational BIOLOGY AND bioinformatics 2018年第2期15卷 350-351页

作者： Dediu, Adrian-Horia Martin-Vide, Carlos Superdata Bucharest Romania Rovira & Virgili Univ Tarragona Spain

This special section of the ieee/ACM Transactions on computational Biology and bioinformatics contains extended versions of the best papers presented at the First International conference on Algorithms for computational Biology (AICoB 2014). Out of 39 submissions to the conference, only four papers representing the current state-of-the-art in their respective domains were accepted to this special section.

关键词： Analysis of algorithms and problem complexity cutting planes endoplasmic reticulum heuristic design machine learning network dynamics next generation sequencing signal processing systems

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A Network-Guided Reaction-Diffusion Model of AT[N] Biomarkers in Alzheimer’s Disease

A Network-Guided Reaction-Diffusion Model of AT[N] Biomarker...

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ieee Symposium on bioinformatics and Bioengineering (BIBE)

作者： Jingwen Zhang Defu Yang Wei He Guorong Wu Minghan Chen Departmment of Computer Science Wake Forest University Winston Salem USA University of North Carolina at Chapel Hill Chapel Hill USA Genetics Bioinformatics and Computational Biology. Virginia Tech Blacksburg USA

ISBN: (数字)9781728195742

ISBN: (纸本)9781728195759

Currently, many studies of Alzheimer's disease (AD) are investigating the neurobiological factors behind the acquisition of beta-amyloid (A), pathologic tau (T), and neurodegeneration ([N]) biomarkers from neuroimages. However, a system-level mechanism of how these neuropathological burdens promote neurodegeneration and why AD exhibits characteristic progression is largely elusive. In this study, we combined the power of systems biology and network neuroscience to understand the dynamic interaction and diffusion process of AT[N] biomarkers from an unprecedented amount of longitudinal Amyloid PET scan, MRI imaging, and DTI data. Specifically, we developed a network-guided biochemical model to jointly (1) model the interaction of AT[N] biomarkers at each brain region and (2) characterize their propagation pattern across the fiber pathways in the structural brain network, where the brain resilience is also considered as a moderator of cognitive decline. Our biochemical model offers a greater mathematical insight to understand the physiopathological mechanism of AD progression by studying the system dynamics and stability. Thus, an in-depth system-level analysis allows us to gain a new understanding of how AT[N] biomarkers spread throughout the brain, capture the early sign of cognitive decline, and predict the AD progression from the preclinical stage.

关键词： Biological system modeling computational modeling systems biology Biomarkers Brain modeling Mathematical model Resilience

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Improve spark-based application performance using bayesian hyperparameter optimization 8

Improve spark-based application performance using bayesian h...

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8th ieee Data Driven Control and Learning systems conference, DDCLS 2019

作者： Li, Kexue Deng, Li Lu, Yakang Wu, Jinda Shanghai Key Laboratory of Power Station Automation Technology Shanghai200072 China

ISBN: (纸本)9781728114545

Metagenomics sequences assembly has an insurmountable obstacle in computational and memory resources limitations. SpaRC, a scalable sequence clustering application using Apache Spark, provides a scalable solution for clustering billions of reads from the next-generation sequencing(NGS) technologies. However, optimizing parameters to achieve better accuracy at this scale becomes very challenging and expensive. Here we explored Bayesian hyperparameter optimization to alleviate this problems by tuning the parameters to achieve near optimal cluster accuracy, without expensive parameter exploration. We report cluster performance on both short reads (Illumina) and long reads (PacBio) sequencing platforms. Results indicates that the methods offers great improvement in clustering performance. We hope insights we gained in this experiment can be generally applied to similar genomics applications based on Spark. © 2019 ieee.

关键词： bioinformatics

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A Quantum-inspired Optimization Heuristic for the Multiple Sequence Alignment Problem in Bio-computing 10

A Quantum-inspired Optimization Heuristic for the Multiple S...

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10th International conference on Information, Intelligence, systems and Applications (IISA)

作者： Giannakis, Konstantinos Papalitsas, Christos Theocharopoulou, Georgia Fanarioti, Sofia Andronikos, Theodore Ionian Univ Dept Informat Corfu Greece

ISBN: (纸本)9781728149592

Data related to biology are characterized by large volume and requirements for enormous computational power. Biological sequences, either of proteins or DNA/RNA segments, can be large and usually need massive computations in order to discover relations and study particular properties Aligning sequences is of great importance for various practical reasons. Multiple sequence alignment studies the problem of aligning several strings resulting in a complete alignment, a problem for which several different approaches exist. In this work, a novel heuristic method to progressively solve this problem is proposed using elements of quantum-inspired optimization. The proposed algorithm is described in detail and evaluated through simulations against other aligning methods. The experimental results seem promising for providing a good initial alignment, especially for the case of large sets of sequences.

关键词： multiple sequence alignment optimization quantum-inspired TSP bio-inspired bio-computing bioinformatics

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A bioinformatics Protocol for Quickly Creating Large-Scale Phylogenetic Trees 12th

A Bioinformatics Protocol for Quickly Creating Large-Scale P...

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12th International conference on Practical Applications of computational Biology and bioinformatics (PACBB)

作者： Lopez-Fernandez, Hugo Duque, Pedro Henriques, Silvia Vazquez, Noe Fdez-Riverola, Florentino Vieira, Cristina P. Reboiro-Jato, Miguel Vieira, Jorge Univ Vigo ESEI Escuela Super Ingn Informat Edificio PolitecnCampus Univ Lagoas S-N Orense 32004 Spain Ctr Singular Invest Galicia Ctr Invest Biomed Vigo Spain SERGAS UVIGO IIS Galicia Sur Galicia Sur Hlth Res Inst SING Res Grp Vigo Spain Univ Porto Inst Invest & Inovacao Saude I3S Rua Alfredo Allen 208 P-4200135 Porto Portugal IBMC Rua Alfredo Allen 208 P-4200135 Porto Portugal Univ Porto Fac Ciencias Rua Campo Alegre 1021-1055 P-4169007 Porto Portugal

ISBN: (纸本)9783319987026;9783319987019

The large scale genome datasets that are now available can provide unprecedented insight into the evolution of genes and gene families. Nevertheless, handling and transforming such datasets into the desired format for downstream analyses is often a difficult and time-consuming task for researchers without a background in informatics. Here, we present a simple and fast protocol for data preparation and high quality phylogenetic tree inferences using simple to install cross-platform software applications with rich graphical interfaces. To illustrate its potential, this protocol was used to provide insight into the evolution of GULO gene in animals, a gene that encodes the enzyme responsible for the last step of vitamin C synthesis in this group of organisms. We find that GULO is always a single copy gene in all animal groups with the exception of Echinodermata. Surprisingly, we find potentially functional GULO genes in several Prostotomian groups such as Molluscs, Priapulida and Arachnida. To our knowledge, this is the first time a putative functional GULO gene is reported in Protostomians. All previously reported GULO gene losses were easily identified using the presented protocol.

关键词： Large scale analyses GULO Animals

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