Construction of phylogenetic tree from multiple gene trees using principal co...IAEME Publication
This document describes a method for constructing a phylogenetic tree from multiple gene trees using principal component analysis. Multiple gene trees are generated from different protein sequences from various organisms. Distance matrices are calculated for each gene tree and combined into a single data matrix. Principal component analysis is performed on the data matrix to extract the first principal component, which represents the consensus distance vector combining information from all gene trees. A phylogenetic tree is then generated from the consensus distance vector using UPGMA, providing a species tree that integrates information from multiple genes. The method is demonstrated on protein sequence data from primates and placental mammals.
This presentation entitled 'Molecular phylogenetics and its application' deals with all the developmental ideas and basics in the field of bioinformatics.
Multiple Sequence Alignment-just glims of viewes on bioinformatics.Arghadip Samanta
Multiple sequence alignment is used to infer evolutionary relationships by comparing homologous sequences. It involves aligning three or more biological sequences, such as protein, DNA, or RNA that are assumed to share a common ancestor. The document discusses methods for multiple sequence alignment including progressive alignment, which builds alignments sequentially according to a guide tree, and divide-and-conquer algorithms, which divide the problem into subproblems. It also describes using the resulting multiple sequence alignment for phylogenetic analysis to construct evolutionary trees and assess shared ancestry among sequences.
This document outlines the process of constructing phylogenetic trees to delineate relationships among Coronaviridae species using protein sequences. It describes:
1) Choosing nucleocapsid and membrane proteins as molecular markers and collecting sequences from NCBI.
2) Performing multiple sequence alignment on the proteins using MUSCLE in MEGA, which is more accurate than ClustalW.
3) Selecting maximum likelihood as the tree-building method because it uses all sequence information without reducing it to distances and makes fewer assumptions than other methods.
Interactomics, Integromics to Systems Biology: Next Animal Biotechnology Fron...Varij Nayan
“Organisms function in an integrated manner-our senses, our muscles, our metabolism and our minds work together seamlessly. But biologists have historically studied organisms part by part and celebrated the modern ability to study them molecule by molecule, gene by gene. Systems biology is critical science of future that seeks to understand the integration of the pieces to form biological
systems”
(David Baltimore, Nobel Laureate)
This document summarizes a dissertation on developing biodegradable scaffolds for tissue engineering using electrospun poly-L-lactide (PLLA) fibers. The study varied electrospinning parameters to control fiber morphology and tested fiber properties. Cell studies showed human cardiac progenitor cells attached to fibers with diameters of 2-3 or 10-11 microns and aligned fibers guided cell orientation. Fiber topology also influenced cell behavior, with random smooth fibers maintaining stemness but allowing osteogenic and adipogenic differentiation, while random rough fibers suppressed differentiation, proliferation and colonization. The dissertation established relationships between scaffold properties, processing parameters and cell responses to inform scaffold design guidelines.
1. Molecular phylogenetics is the study of evolutionary relationships among biological entities using molecular data like DNA, RNA, and protein sequences.
2. The first phylogenetic tree based on molecular data was constructed in 1967 by Fitch and Margoliash. This helped establish the significance of molecular evidence in taxonomy.
3. Phylogenetic studies use molecular techniques to assess historical evolutionary relationships, while phylogeographic studies examine geographic distributions of species. Molecular data revolutionized our understanding of evolutionary relationships.
This document discusses phylogenetic analysis and taxonomy. It introduces key terms and concepts related to phylogeny and classification, including that all species can be viewed as branches on the tree of life. It explains that phylogenetic analysis studies evolutionary relationships between species, and is informed by morphological and molecular data. The document also discusses how phylogenetic trees are hypotheses about evolutionary descent that can be tested against independent sources of data.
Construction of phylogenetic tree from multiple gene trees using principal co...IAEME Publication
This document describes a method for constructing a phylogenetic tree from multiple gene trees using principal component analysis. Multiple gene trees are generated from different protein sequences from various organisms. Distance matrices are calculated for each gene tree and combined into a single data matrix. Principal component analysis is performed on the data matrix to extract the first principal component, which represents the consensus distance vector combining information from all gene trees. A phylogenetic tree is then generated from the consensus distance vector using UPGMA, providing a species tree that integrates information from multiple genes. The method is demonstrated on protein sequence data from primates and placental mammals.
This presentation entitled 'Molecular phylogenetics and its application' deals with all the developmental ideas and basics in the field of bioinformatics.
Multiple Sequence Alignment-just glims of viewes on bioinformatics.Arghadip Samanta
Multiple sequence alignment is used to infer evolutionary relationships by comparing homologous sequences. It involves aligning three or more biological sequences, such as protein, DNA, or RNA that are assumed to share a common ancestor. The document discusses methods for multiple sequence alignment including progressive alignment, which builds alignments sequentially according to a guide tree, and divide-and-conquer algorithms, which divide the problem into subproblems. It also describes using the resulting multiple sequence alignment for phylogenetic analysis to construct evolutionary trees and assess shared ancestry among sequences.
This document outlines the process of constructing phylogenetic trees to delineate relationships among Coronaviridae species using protein sequences. It describes:
1) Choosing nucleocapsid and membrane proteins as molecular markers and collecting sequences from NCBI.
2) Performing multiple sequence alignment on the proteins using MUSCLE in MEGA, which is more accurate than ClustalW.
3) Selecting maximum likelihood as the tree-building method because it uses all sequence information without reducing it to distances and makes fewer assumptions than other methods.
Interactomics, Integromics to Systems Biology: Next Animal Biotechnology Fron...Varij Nayan
“Organisms function in an integrated manner-our senses, our muscles, our metabolism and our minds work together seamlessly. But biologists have historically studied organisms part by part and celebrated the modern ability to study them molecule by molecule, gene by gene. Systems biology is critical science of future that seeks to understand the integration of the pieces to form biological
systems”
(David Baltimore, Nobel Laureate)
This document summarizes a dissertation on developing biodegradable scaffolds for tissue engineering using electrospun poly-L-lactide (PLLA) fibers. The study varied electrospinning parameters to control fiber morphology and tested fiber properties. Cell studies showed human cardiac progenitor cells attached to fibers with diameters of 2-3 or 10-11 microns and aligned fibers guided cell orientation. Fiber topology also influenced cell behavior, with random smooth fibers maintaining stemness but allowing osteogenic and adipogenic differentiation, while random rough fibers suppressed differentiation, proliferation and colonization. The dissertation established relationships between scaffold properties, processing parameters and cell responses to inform scaffold design guidelines.
1. Molecular phylogenetics is the study of evolutionary relationships among biological entities using molecular data like DNA, RNA, and protein sequences.
2. The first phylogenetic tree based on molecular data was constructed in 1967 by Fitch and Margoliash. This helped establish the significance of molecular evidence in taxonomy.
3. Phylogenetic studies use molecular techniques to assess historical evolutionary relationships, while phylogeographic studies examine geographic distributions of species. Molecular data revolutionized our understanding of evolutionary relationships.
This document discusses phylogenetic analysis and taxonomy. It introduces key terms and concepts related to phylogeny and classification, including that all species can be viewed as branches on the tree of life. It explains that phylogenetic analysis studies evolutionary relationships between species, and is informed by morphological and molecular data. The document also discusses how phylogenetic trees are hypotheses about evolutionary descent that can be tested against independent sources of data.
20080516 Spontaneous separation of bi-stable biochemical systemsJonathan Blakes
The document discusses bi-stable biochemical systems that can spontaneously separate into spatial domains with opposite states due to stochastic fluctuations, even within small volumes like bacteria. It introduces the Next Subvolume Method for simulating these systems by partitioning volumes into well-mixed subvolumes and accounting for diffusion between them. Shape, diffusion rates, and geometry can influence whether and where spatial separation occurs.
This document provides an overview of sequence analysis, including:
1) Defining sequence analysis as subjecting DNA, RNA, or peptide sequences to analytical methods to understand features, function, structure, or evolution.
2) Applications of sequence analysis like comparing sequences to find similarity and identify intrinsic features.
3) Methods of DNA and protein sequencing like Sanger sequencing, pyrosequencing, and Edman degradation.
Survey of softwares for phylogenetic analysisArindam Ghosh
The document discusses the process of phylogenetic analysis using cytochrome c oxidase subunit 1 (COX1) gene sequences from several organisms: human, bovine, zebrafish, pig, and sheep. It provides the COX1 protein sequences for each organism downloaded from UniProt. The sequences will be aligned using Clustal Omega and a phylogenetic tree will be constructed using Clustal W2 to analyze the evolutionary relationships between the organisms.
The document presents a computational model that simulates the transport of putative cytokinesis signaling proteins along microtubules (MTs) in dividing cells. The model represents signaling proteins as particles that can move short distances along MTs via a plus-end directed motor or diffuse freely in the cytoplasm. Simulations show that MTs from the spindle can guide these signaling particles to accumulate over time at the equatorial cortex, consistent with the equatorial stimulation model of cytokinesis. The authors validate this model experimentally by observing cell division patterns in sea urchin embryos with manipulated shapes. The findings support a mechanism by which MT-based transport localizes cytokinesis factors to the future division site.
The role of machine learning in modelling the cellbutest
The document discusses the role of machine learning in modelling the cell. It provides an overview of cell biology and challenges in modelling the cell. It then discusses machine learning techniques like neural networks that can be used to model biological sequences and patterns. Specifically, it discusses how recurrent neural networks have been applied to predict subcellular localization of proteins to organelles like the endoplasmic reticulum and peroxisomes.
1) Interactomics is the study of interactions between genes or proteins, including genetic and physical interactions.
2) Complementation groups can identify mutations in the same or different genes involved in the same pathway through genetic crosses of mutant organisms.
3) Modifier screens uncover new genes involved in a biological pathway by identifying mutations that alter the phenotype of an original mutant. Mapping protein-protein interaction networks provides a framework for understanding biology as an integrated system.
A Systems Biology Approach to Natural Products ResearchHuda Nazeer
Explains the systems biology approach (holistic approach), its advantages and tools used compared to the reductionist approach in natural products research.
This document discusses phylogenetic tree construction using distance-based methods. It begins by introducing phylogenetic trees and their use in fields like forensics, disease prediction, and drug discovery. It then outlines the basic steps to construct a phylogenetic tree: sequence alignment, distance calculation, and tree verification. The main distance-based approaches covered are UPGMA, Neighbor-Joining, Fitch-Margoliash, Minimum Evolution. Each method calculates genetic distances differently and has advantages and limitations for reconstructing evolutionary relationships from sequence data.
Systems biology - Bioinformatics on complete biological systemsLars Juhl Jensen
This document discusses systems biology and bioinformatics. It describes how systems biology takes a holistic approach to study complete biological systems and all of their components and interactions. In contrast, earlier approaches in biology focused on studying one gene or protein at a time. The document outlines several key subfields and approaches within systems biology, including mathematical modeling of biological networks and pathways, data integration from various sources, and the use of association networks to predict functional relationships between biomolecules. It provides examples of publicly available databases like STRING and STITCH that compile interaction and association data from multiple sources for large numbers of organisms. The challenges of data integration are also discussed due to issues like incompatible identifiers and variable data quality across sources. The document then focuses on
This document discusses DNA sequencing and phylogenetic analysis. It defines DNA sequencing as determining the order of nucleotide bases in a DNA molecule. It describes several DNA sequencing techniques like Sanger sequencing and nanopore sequencing. It explains how DNA sequencing results are used to infer phylogenetic relationships and construct phylogenetic trees showing evolutionary relationships among species. It discusses applications of DNA sequencing and phylogenetic analysis in fields like medicine, forensics, and tracing pathogen evolution.
The cellular cytoskeleton is essential in proper cell function as well as in organism development. These polymers provide the elaborate roads along which most intracellular protein transport occurs. I will discuss several examples where mathematical modeling, analysis, and simulation tools help us study and understand the interactions between these filaments roads and motor proteins in cells. In neurons, neurofilaments navigate axons and their constrictions to maintain a healthy speed of neuronal communication. We develop stochastic models that may provide insights into transport mechanisms through axonal constrictions. In the reproductive system of the worm C. elegans, we use agent - based modeling to study how myosin motors interact with actin filaments to maintain contractile rings that allow passage and nutrient transport for developing egg cells. In addition, we have recently become interested in using topological data analysis tools to assess maintenance and establishment of these ring structures.
Large-scale generation of mathematical models from biological pathways
This document discusses the large-scale generation of mathematical models from biological pathway data. Pathway data from databases are converted into models using standardized formats and modeling languages. Over 100,000 models of metabolic networks and 27,000 models of signaling pathways have been generated in SBML format. These models provide a starting point for systems-level modeling and simulation of biochemical pathways across many species. The workflow involves translating pathways into activity flows, logical models, and flux balance models using common modeling approaches and rate laws.
Raman microscopy and x ray diffraction a combined study of fibrillin-rich mic...John Clarkson
J.L. Haston, S.B. Engelsen, M. Roessle, J. Clarkson, E.W. Blanch, C. Baldock, C.M. Kielty & T.J. Wess, “Raman microscopy and X-ray diffraction: A combined study of fibrillin-rich microfibillar elasticity”, J. Biol. Chem., 278(42), 41189-41197, 2003.
Systems biology: Bioinformatics on complete biological systemLars Juhl Jensen
Systems biology uses mathematical modeling to study molecular networks and complete biological systems. It requires detailed knowledge of molecular interactions, which can be determined through various high-throughput interaction assays. However, interaction data from different databases may have varying quality and identifiers, so integrating this data requires resolving these issues. Natural language processing of literature can provide additional interaction data by recognizing named entities and extracting relations from text.
The document describes a model of mitochondrial fusion using membrane automata. It investigates the biological function of mitochondrial fusion and models it using membrane automata and brane calculus. The model combines P automata and BioAmbients calculus to represent the hierarchical membrane structure and biomolecular rules governing mitochondrial fusion. It translates the biological model of fusion expressed in BioAmbient calculus into rewriting rules of P automata to simulate the process in a more visual and well-established framework.
The document discusses different types of sequence analysis and alignment methods. It describes analyzing DNA, RNA, and protein sequences to understand their features, functions, and evolution. Methods include aligning sequences globally or locally to identify similar regions. Pairwise alignment involves two sequences while multiple sequence alignment incorporates more sequences using techniques like dynamic programming, progressive alignment, and motif finding. Structural alignments also use 3D protein or RNA structure information.
This document discusses phylogeny, which is the study of evolutionary relationships among organisms. It describes how phylogeny is represented diagrammatically through phylogenetic trees, which can be rooted or unrooted. There are two main methods for constructing phylogenetic trees - character-based methods like maximum parsimony and maximum likelihood, and distance-based methods like UPGMA and neighbor joining. The document also discusses cladistics and how cladograms differ from phylogenetic trees in representing evolutionary relationships.
This document discusses systems biology approaches to studying cancer. It defines systems biology as studying organisms as interacting networks of genes, proteins, and reactions. Biological networks are constructed from different types of data and relationships. Integrating multiple data types into networks can provide a more complete understanding of cancer than single data types in isolation. Networks can be used to identify cancer driver genes, dysregulated pathways, and biomarkers for disease classification, understanding mechanisms, and drug development. While current biological networks are incomplete, systems approaches have already provided insights and are expected to be more powerful as networks become more comprehensive.
Phylogenetic prediction - maximum parsimony methodAfnan Zuiter
This document discusses the maximum parsimony method for phylogenetic prediction. It minimizes the number of evolutionary changes needed to produce observed genetic variations between sequences. A multiple sequence alignment is required to identify corresponding positions, which are analyzed to find the tree(s) requiring the fewest evolutionary changes overall. It is best for small numbers of similar sequences but becomes computationally intensive with many diverse sequences. Software like PAUP automates maximum parsimony analysis.
Experimental Research on Primary Wave Height Generated by Integral Landslide ...Agriculture Journal IJOEAR
1) The document describes an experimental study on primary wave height generated by landslides entering a channel-type reservoir. Orthogonal experimental design was used to simulate landslides of varying length, thickness, water depth, entry angle, and head.
2) Measurement of primary wave height in 18 experimental groups found water depth had the greatest effect, followed by landslide thickness, entry angle, and length. Landslide head had a minimal effect.
3) Theoretical analysis found landslide entry speed, and thus primary wave height, was closely related to entry angle and landslide height. However, the small variation in landslide head in the experiment meant it could be ignored as an influencing factor.
Fung, Y.C. "A First Course in Continuum Mechanics, Third Edition", Ed. Prenti...xyz666
The document discusses the history and development of artificial intelligence over the past several decades. It outlines milestones in AI such as the creation of expert systems in the 1980s and advances in machine learning and deep learning since 2010 that have enabled intelligent assistants, self-driving cars, and other applications. The document suggests AI will continue to progress and have widespread societal impacts.
20080516 Spontaneous separation of bi-stable biochemical systemsJonathan Blakes
The document discusses bi-stable biochemical systems that can spontaneously separate into spatial domains with opposite states due to stochastic fluctuations, even within small volumes like bacteria. It introduces the Next Subvolume Method for simulating these systems by partitioning volumes into well-mixed subvolumes and accounting for diffusion between them. Shape, diffusion rates, and geometry can influence whether and where spatial separation occurs.
This document provides an overview of sequence analysis, including:
1) Defining sequence analysis as subjecting DNA, RNA, or peptide sequences to analytical methods to understand features, function, structure, or evolution.
2) Applications of sequence analysis like comparing sequences to find similarity and identify intrinsic features.
3) Methods of DNA and protein sequencing like Sanger sequencing, pyrosequencing, and Edman degradation.
Survey of softwares for phylogenetic analysisArindam Ghosh
The document discusses the process of phylogenetic analysis using cytochrome c oxidase subunit 1 (COX1) gene sequences from several organisms: human, bovine, zebrafish, pig, and sheep. It provides the COX1 protein sequences for each organism downloaded from UniProt. The sequences will be aligned using Clustal Omega and a phylogenetic tree will be constructed using Clustal W2 to analyze the evolutionary relationships between the organisms.
The document presents a computational model that simulates the transport of putative cytokinesis signaling proteins along microtubules (MTs) in dividing cells. The model represents signaling proteins as particles that can move short distances along MTs via a plus-end directed motor or diffuse freely in the cytoplasm. Simulations show that MTs from the spindle can guide these signaling particles to accumulate over time at the equatorial cortex, consistent with the equatorial stimulation model of cytokinesis. The authors validate this model experimentally by observing cell division patterns in sea urchin embryos with manipulated shapes. The findings support a mechanism by which MT-based transport localizes cytokinesis factors to the future division site.
The role of machine learning in modelling the cellbutest
The document discusses the role of machine learning in modelling the cell. It provides an overview of cell biology and challenges in modelling the cell. It then discusses machine learning techniques like neural networks that can be used to model biological sequences and patterns. Specifically, it discusses how recurrent neural networks have been applied to predict subcellular localization of proteins to organelles like the endoplasmic reticulum and peroxisomes.
1) Interactomics is the study of interactions between genes or proteins, including genetic and physical interactions.
2) Complementation groups can identify mutations in the same or different genes involved in the same pathway through genetic crosses of mutant organisms.
3) Modifier screens uncover new genes involved in a biological pathway by identifying mutations that alter the phenotype of an original mutant. Mapping protein-protein interaction networks provides a framework for understanding biology as an integrated system.
A Systems Biology Approach to Natural Products ResearchHuda Nazeer
Explains the systems biology approach (holistic approach), its advantages and tools used compared to the reductionist approach in natural products research.
This document discusses phylogenetic tree construction using distance-based methods. It begins by introducing phylogenetic trees and their use in fields like forensics, disease prediction, and drug discovery. It then outlines the basic steps to construct a phylogenetic tree: sequence alignment, distance calculation, and tree verification. The main distance-based approaches covered are UPGMA, Neighbor-Joining, Fitch-Margoliash, Minimum Evolution. Each method calculates genetic distances differently and has advantages and limitations for reconstructing evolutionary relationships from sequence data.
Systems biology - Bioinformatics on complete biological systemsLars Juhl Jensen
This document discusses systems biology and bioinformatics. It describes how systems biology takes a holistic approach to study complete biological systems and all of their components and interactions. In contrast, earlier approaches in biology focused on studying one gene or protein at a time. The document outlines several key subfields and approaches within systems biology, including mathematical modeling of biological networks and pathways, data integration from various sources, and the use of association networks to predict functional relationships between biomolecules. It provides examples of publicly available databases like STRING and STITCH that compile interaction and association data from multiple sources for large numbers of organisms. The challenges of data integration are also discussed due to issues like incompatible identifiers and variable data quality across sources. The document then focuses on
This document discusses DNA sequencing and phylogenetic analysis. It defines DNA sequencing as determining the order of nucleotide bases in a DNA molecule. It describes several DNA sequencing techniques like Sanger sequencing and nanopore sequencing. It explains how DNA sequencing results are used to infer phylogenetic relationships and construct phylogenetic trees showing evolutionary relationships among species. It discusses applications of DNA sequencing and phylogenetic analysis in fields like medicine, forensics, and tracing pathogen evolution.
The cellular cytoskeleton is essential in proper cell function as well as in organism development. These polymers provide the elaborate roads along which most intracellular protein transport occurs. I will discuss several examples where mathematical modeling, analysis, and simulation tools help us study and understand the interactions between these filaments roads and motor proteins in cells. In neurons, neurofilaments navigate axons and their constrictions to maintain a healthy speed of neuronal communication. We develop stochastic models that may provide insights into transport mechanisms through axonal constrictions. In the reproductive system of the worm C. elegans, we use agent - based modeling to study how myosin motors interact with actin filaments to maintain contractile rings that allow passage and nutrient transport for developing egg cells. In addition, we have recently become interested in using topological data analysis tools to assess maintenance and establishment of these ring structures.
Large-scale generation of mathematical models from biological pathways
This document discusses the large-scale generation of mathematical models from biological pathway data. Pathway data from databases are converted into models using standardized formats and modeling languages. Over 100,000 models of metabolic networks and 27,000 models of signaling pathways have been generated in SBML format. These models provide a starting point for systems-level modeling and simulation of biochemical pathways across many species. The workflow involves translating pathways into activity flows, logical models, and flux balance models using common modeling approaches and rate laws.
Raman microscopy and x ray diffraction a combined study of fibrillin-rich mic...John Clarkson
J.L. Haston, S.B. Engelsen, M. Roessle, J. Clarkson, E.W. Blanch, C. Baldock, C.M. Kielty & T.J. Wess, “Raman microscopy and X-ray diffraction: A combined study of fibrillin-rich microfibillar elasticity”, J. Biol. Chem., 278(42), 41189-41197, 2003.
Systems biology: Bioinformatics on complete biological systemLars Juhl Jensen
Systems biology uses mathematical modeling to study molecular networks and complete biological systems. It requires detailed knowledge of molecular interactions, which can be determined through various high-throughput interaction assays. However, interaction data from different databases may have varying quality and identifiers, so integrating this data requires resolving these issues. Natural language processing of literature can provide additional interaction data by recognizing named entities and extracting relations from text.
The document describes a model of mitochondrial fusion using membrane automata. It investigates the biological function of mitochondrial fusion and models it using membrane automata and brane calculus. The model combines P automata and BioAmbients calculus to represent the hierarchical membrane structure and biomolecular rules governing mitochondrial fusion. It translates the biological model of fusion expressed in BioAmbient calculus into rewriting rules of P automata to simulate the process in a more visual and well-established framework.
The document discusses different types of sequence analysis and alignment methods. It describes analyzing DNA, RNA, and protein sequences to understand their features, functions, and evolution. Methods include aligning sequences globally or locally to identify similar regions. Pairwise alignment involves two sequences while multiple sequence alignment incorporates more sequences using techniques like dynamic programming, progressive alignment, and motif finding. Structural alignments also use 3D protein or RNA structure information.
This document discusses phylogeny, which is the study of evolutionary relationships among organisms. It describes how phylogeny is represented diagrammatically through phylogenetic trees, which can be rooted or unrooted. There are two main methods for constructing phylogenetic trees - character-based methods like maximum parsimony and maximum likelihood, and distance-based methods like UPGMA and neighbor joining. The document also discusses cladistics and how cladograms differ from phylogenetic trees in representing evolutionary relationships.
This document discusses systems biology approaches to studying cancer. It defines systems biology as studying organisms as interacting networks of genes, proteins, and reactions. Biological networks are constructed from different types of data and relationships. Integrating multiple data types into networks can provide a more complete understanding of cancer than single data types in isolation. Networks can be used to identify cancer driver genes, dysregulated pathways, and biomarkers for disease classification, understanding mechanisms, and drug development. While current biological networks are incomplete, systems approaches have already provided insights and are expected to be more powerful as networks become more comprehensive.
Phylogenetic prediction - maximum parsimony methodAfnan Zuiter
This document discusses the maximum parsimony method for phylogenetic prediction. It minimizes the number of evolutionary changes needed to produce observed genetic variations between sequences. A multiple sequence alignment is required to identify corresponding positions, which are analyzed to find the tree(s) requiring the fewest evolutionary changes overall. It is best for small numbers of similar sequences but becomes computationally intensive with many diverse sequences. Software like PAUP automates maximum parsimony analysis.
Experimental Research on Primary Wave Height Generated by Integral Landslide ...Agriculture Journal IJOEAR
1) The document describes an experimental study on primary wave height generated by landslides entering a channel-type reservoir. Orthogonal experimental design was used to simulate landslides of varying length, thickness, water depth, entry angle, and head.
2) Measurement of primary wave height in 18 experimental groups found water depth had the greatest effect, followed by landslide thickness, entry angle, and length. Landslide head had a minimal effect.
3) Theoretical analysis found landslide entry speed, and thus primary wave height, was closely related to entry angle and landslide height. However, the small variation in landslide head in the experiment meant it could be ignored as an influencing factor.
Fung, Y.C. "A First Course in Continuum Mechanics, Third Edition", Ed. Prenti...xyz666
The document discusses the history and development of artificial intelligence over the past several decades. It outlines milestones in AI such as the creation of expert systems in the 1980s and advances in machine learning and deep learning since 2010 that have enabled intelligent assistants, self-driving cars, and other applications. The document suggests AI will continue to progress and have widespread societal impacts.
The document discusses key statistical terms used in analyzing portfolio performance including mean, standard deviation, variance, correlation coefficient, and normal distribution. It explains how mean measures average returns, variance and standard deviation measure risk/volatility, and correlation measures the relationship between two investments. The document also covers portfolio theory, the efficient frontier, and risk/return analysis tools like the Sharpe Ratio and Value at Risk (VAR) that are used to evaluate portfolio performance based on expected return and risk.
The document discusses the relationship between risk and return when investing. It states that there is a trade-off between expected risk and expected return, with higher risk investments typically offering higher returns to compensate investors for taking on more risk. It also discusses how diversification across multiple assets can reduce the non-systematic/diversifiable risk in a portfolio, but not the systematic/market risk that is related to movements in the overall market. The document defines beta as a measure of a stock's systematic risk relative to the market.
The document discusses quality assurance and control. It emphasizes the importance of quality assurance and control in improving customer satisfaction and conforming to specifications. It outlines several key aspects of quality assurance including quality planning, assurance, and control. It also discusses how to integrate quality assurance with customer satisfaction and conformance to requirements.
This document presents a methodological pipeline to analyze the morphological diversity and evolution of marine tetrapods using multiple techniques:
1. Morphometric analyses of extinct and living marine tetrapods to numerically describe their diversity and derive a theoretical morphospace.
2. Computational fluid dynamic simulations to quantify functional parameters like lift, drag, and pressure around bodies under different conditions.
3. Phylogenetic comparative methods and morphospace analyses to test hypotheses about contingency vs. determinism in evolution by examining patterns of morphological convergence and disparity.
The goal is to gain insights into marine tetrapod evolution and the degree of determinism or flexibility in exploring morphological design space.
The Algorithms of Life - Scientific Computing for Systems Biologyinside-BigData.com
In this deck from ISC 2019, Ivo Sbalzarini from TU Dresden presents: The Algorithms of Life - Scientific Computing for Systems Biology. In his talk, Sbalzarini mainly discussed the rapidly growing importance and influence in the life sciences for scientific high-performance computing.
"Scientific high-performance computing is of rapidly growing importance and influence in the life sciences. Thanks to the increasing knowledge about the molecular foundations of life, recent advances in biomedical data science, and the availability of predictive biophysical theories that can be numerically simulated, mechanistic understanding of the emergence of life comes within reach. Computing is playing a pivotal and catalytic role in this scientific revolution, both as a tool of investigation and hypothesis testing, but also as a school of thought and systems model. This is because a developing tissue, embryo, or organ can itself be seen as a massively parallel distributed computing system that collectively self-organizes to bring about behavior we call life. In any multicellular organism, every cell constantly takes decisions about growth, division, and migration based on local information, with cells communicating with each other via chemical, mechanical, and electrical signals across length scales from nanometers to meters. Each cell can therefore be understood as a mechano-chemical processing element in a complexly interconnected million- or billion-core computing system. Mechanistically understanding and reprogramming this system is a grand challenge. While the “hardware” (proteins, lipids, etc.) and the “source code” (genetic code) are increasingly known, we known virtually nothing about the algorithms that this code implements on this hardware. Our vision is to contribute to this challenge by developing computational methods and software systems for high-performance data analysis, inference, and numerical simulation of computer models of biological tissues, incorporating the known biochemistry and biophysics in 3D-space and time, in order to understand biological processes on an algorithmic basis. This ranges from real-time approaches to biomedical image analysis, to novel simulation languages for parallel high-performance computing, to virtual reality and machine learning for 3D microscopy and numerical simulations of coupled biochemical-biomechanical models. The cooperative, interdisciplinary effort to develop and advance our understanding of life using computational approaches not only places high-performance computing center stage, but also provides stimulating impulses for the future development of this field."
Watch the video: https://wp.me/p3RLHQ-kBB
Learn more: https://www.isc-hpc.com/
Sign up for our insideHPC Newsletter: http://insidehpc.com/newsletter
large data set is not available for some disease such as Brain Tumor. This and part2 presentation shows how to find "Actionable solution from a difficult cancer dataset
The document describes a cybernetic framework for modeling shoot-root coordinated development in grasses. It proposes that grass morphology emerges from self-organized processes at the modular level rather than central genetic control. A 3D simulator was built using L-systems to represent grass morphogenesis as the recursive behavior of phytomers according to local information. Simulation results demonstrated the model's ability to represent different grass morphotypes and responses to cutting and water availability. The model supports the idea that grass morphogenesis involves distributed regulatory processes rather than single genetic determinants.
Modeling evolution in the classroom: The case of Fukushima’s mutant butterfliesAmyLark
Science education in the United States is evolving. New standards and reform recommendations spanning grades K-16 focus on a limited set of key scientific concepts from each discipline that all students should know but emphasize integrating these with science practices so that students learn not only the “what” of science but also the “how” and “why”. In line with this approach, we present an exercise that models the integration of fundamental evolutionary concepts with science practices. Students use Avida-ED digital evolution software to test claims from a study on mutated butterflies in the vicinity of the compromised Fukushima Daiichi Nuclear Power Plant complex subsequent to the Great East Japan Earthquake of 2011 (Hiyama et al., Scientific Reports 2 Article 570, 2012) to determine the effects of mutation rate on the genomes of individual organisms. This exercise is appropriate for use in both high school and undergraduate biology classrooms.
THE ISSUE OF UNCERTAINTY FOR HYDROLOGIC EVENTS IN THE MISSOURI RIVER WATERSHE...Boris Shmagin
1. The document discusses a paradigm shift in science and methodology due to computers, with concepts moving from a simple to complex world. Pattern recognition problems in cognitive science helped develop new methods.
2. The new paradigm introduces direct search for solutions, emphasis on decision making, and a unity of technical and holistic languages for pattern description. This leads to a convergence of exact science and humanities.
3. The main difference between the new and old paradigms is a focus on controlling algorithm complexity rather than function complexity to guarantee inference success. Low complexity algorithms can create complex functions that generalize well.
This document summarizes a research study that developed a data-driven model of zebrafish social behavior accounting for both speed and turning interactions among fish. The model was used to analyze how an "informed" agent that actively modulates its speed can entrain and stabilize the collective dynamics of a naive shoal. Force mapping analysis of experimental zebrafish pair data revealed that speed interactions depend on front-back distance while turning depends on left-right distance. The model incorporates these interactions through response functions in the stochastic differential equations governing individual fish motion. Simulations show that an informed agent able to actively modulate its speed can lead and stabilize naive shoal dynamics more effectively than one moving at constant speed.
Analysis of Existing Models in Relation to the Problems of Mass Exchange betw...YogeshIJTSRD
The main recommendations of this article mainly analyzing the rate of harmful elements the period of exploitation of the automobile implements and its services to develop activity of automobile implements of the exploitation period. Shavkat Giyazov "Analysis of Existing Models in Relation to the Problems of Mass Exchange between Autotransport Complex and the Environment" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-3 , April 2021, URL: https://www.ijtsrd.com/papers/ijtsrd38681.pdf Paper URL: https://www.ijtsrd.com/engineering/automotive-engineering/38681/analysis-of-existing-models-in-relation-to-the-problems-of-mass-exchange-between-autotransport-complex-and-the-environment/shavkat-giyazov
Characterizing, Modelling and Simulating Naturally Fractured Reservoirs - Stu...Total Campus
This document summarizes challenges in modeling naturally fractured reservoirs (NFRs). NFRs are characterized by a coexistence of a fracture network and rock matrix with different properties. Modeling NFRs is complex due to heterogeneous fracture distributions that impact fluid flow at multiple scales. Key challenges include: (1) determining the important fracture scales that drive flow, (2) characterizing fractures near wells to define the flow network, and (3) extrapolating static and dynamic fracture parameters across fields while representing multiscale flow networks with available data. Overcoming these challenges requires integrating well data, geology, geomechanics, and production data to build a full-field fracturing concept and flow model.
Michael Farina presented on establishing new upper bounds for the k-distance domination numbers of grid graphs by generalizing an existing construction of dominating sets to k-distance dominating sets. Armando Grez examined a method for constructing fullerene patches with 4 pentagonal faces and produced an exact process for drawing them. Darleen Perez-Lavin partitioned the set of permutations with a peak set into subsets ending with an ascent or descent and provided formulas to enumerate these subsets for Coxeter groups of types B and D.
The document describes a computational model of early mouse ovarian development using a cellular Potts model. The model simulates the migration of primordial germ cells into the gonadal ridge and their proliferation into germ cell nests and follicles. Key parameters like cell adhesion, growth, apoptosis and signaling molecule concentrations are modeled based on literature. The model is tuned by comparing simulations to experimental data. The goals are to understand normal development, identify biological perturbations, and provide a framework for toxicity testing alternatives.
Topological Data Analysis What is it? What is it good for? How can it be use...DanChitwood
Topological data analysis is a technique that can be used to study plant morphology. It involves using tools from topology and algebraic geometry to analyze shapes and structures. Persistent homology in particular allows researchers to quantify topological features like blobs, holes, and voids that remain consistent under deformations. These techniques have been applied to study plant branching architectures, leaf shapes and serrations, and can provide a way to universally measure plant morphology across scales.
Dr Lael Parrott at the Landscape Science Cluster Seminar, May 2009pdalby
This document summarizes how concepts from complex systems studies can inform natural resource management. It discusses how ecosystems and landscapes are complex systems with emergent properties arising from local interactions. Agent-based models are useful for modeling ecological complexity across scales. Examples shown include a model of grassland resilience under disturbance and the relationship between grazing and spatial complexity. Understanding community assembly is explored through a spatial model linking local communities. The document concludes that embracing complexity requires new tools like multi-scale models and monitoring to manage social-ecological systems.
This document is a thesis presented by Alexandra Mariela Popa to the University Claude Bernard - Lyon 1 in 2011 for the degree of Doctor of Philosophy. It examines the evolution of recombination and genomic structures through a modeling approach. The thesis analyzes the relationships between the causes, characteristics, and effects of recombination from an evolutionary perspective. Models are developed to compare recombination strategies across species and sexes, study the impact of sex-specific recombination hotspots on GC content evolution, and analyze the impact of recombination on deleterious mutation frequencies in human populations.
Presented at Journal Paper Track, The Web Conference, Lyon, France, April 15, 2018
https://doi.org/10.1145/3184558.3186234
Abstract: Linked Open Data (LOD) technology enables web of data and exchangeable knowledge graphs through the Internet. However, the change in knowledge is happened everywhere and every time, and it becomes a challenging issue of linking data precisely because the misinterpretation and misunderstanding of some terms and concepts may be dissimilar under different context of time and different community knowledge. To solve this issue, we introduce an approach to the preservation of knowledge graph, and we select the biodiversity domain to be our case studies because knowledge of this domain is commonly changed and all changes are clearly documented. Our work produces an ontology, transformation rules, and an application to demonstrate that it is feasible to present and preserve knowledge graphs and provides open and accurate access to linked data. It covers changes in names and their relationships from different time and communities as can be seen in the cases of taxonomic knowledge.
1. The document presents a comparison of optical flow methods for estimating motion at subcellular, cellular, and supracellular levels from microscopy images.
2. Synthetic model structures and biological samples are used to evaluate the performance of different optical flow techniques, including Lucas-Kanade, Horn-Schunck, multi-scale Horn-Schunck, and Combined Local-Global.
3. The results demonstrate that multi-scale techniques improve the detectable motion range, and Combined Local-Global performance is comparable to other methods. Parameter optimization and error analysis provide guidance for experimental design.
This document discusses the concept of morphogenetic engineering, which aims to design artificial self-organized systems capable of developing elaborate architectures without central planning. It begins by looking at natural complex systems like animal flocking and termite mounds that self-organize. The focus is on "architectures without architects" in biological systems. Morphogenetic engineering is proposed as a new type of engineering that designs self-organizing agents, not the architectures directly, taking inspiration from embryogenesis, simulated development and synthetic biology. Several research projects are summarized that aim to model biological development and create modular, programmable artificial self-construction.
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Reimagining Your Library Space: How to Increase the Vibes in Your Library No ...Diana Rendina
Librarians are leading the way in creating future-ready citizens – now we need to update our spaces to match. In this session, attendees will get inspiration for transforming their library spaces. You’ll learn how to survey students and patrons, create a focus group, and use design thinking to brainstorm ideas for your space. We’ll discuss budget friendly ways to change your space as well as how to find funding. No matter where you’re at, you’ll find ideas for reimagining your space in this session.
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আমাদের সবার জন্য খুব খুব গুরুত্বপূর্ণ একটি বই ..বিসিএস, ব্যাংক, ইউনিভার্সিটি ভর্তি ও যে কোন প্রতিযোগিতা মূলক পরীক্ষার জন্য এর খুব ইম্পরট্যান্ট একটি বিষয় ...তাছাড়া বাংলাদেশের সাম্প্রতিক যে কোন ডাটা বা তথ্য এই বইতে পাবেন ...
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This presentation includes basic of PCOS their pathology and treatment and also Ayurveda correlation of PCOS and Ayurvedic line of treatment mentioned in classics.
Main Java[All of the Base Concepts}.docxadhitya5119
This is part 1 of my Java Learning Journey. This Contains Custom methods, classes, constructors, packages, multithreading , try- catch block, finally block and more.
This document provides an overview of wound healing, its functions, stages, mechanisms, factors affecting it, and complications.
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There are 4 phases of wound healing: hemostasis, inflammation, proliferation, and remodeling. This document also describes the mechanism of wound healing. Factors that affect healing include infection, uncontrolled diabetes, poor nutrition, age, anemia, the presence of foreign bodies, etc.
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Chapter wise All Notes of First year Basic Civil Engineering.pptxDenish Jangid
Chapter wise All Notes of First year Basic Civil Engineering
Syllabus
Chapter-1
Introduction to objective, scope and outcome the subject
Chapter 2
Introduction: Scope and Specialization of Civil Engineering, Role of civil Engineer in Society, Impact of infrastructural development on economy of country.
Chapter 3
Surveying: Object Principles & Types of Surveying; Site Plans, Plans & Maps; Scales & Unit of different Measurements.
Linear Measurements: Instruments used. Linear Measurement by Tape, Ranging out Survey Lines and overcoming Obstructions; Measurements on sloping ground; Tape corrections, conventional symbols. Angular Measurements: Instruments used; Introduction to Compass Surveying, Bearings and Longitude & Latitude of a Line, Introduction to total station.
Levelling: Instrument used Object of levelling, Methods of levelling in brief, and Contour maps.
Chapter 4
Buildings: Selection of site for Buildings, Layout of Building Plan, Types of buildings, Plinth area, carpet area, floor space index, Introduction to building byelaws, concept of sun light & ventilation. Components of Buildings & their functions, Basic concept of R.C.C., Introduction to types of foundation
Chapter 5
Transportation: Introduction to Transportation Engineering; Traffic and Road Safety: Types and Characteristics of Various Modes of Transportation; Various Road Traffic Signs, Causes of Accidents and Road Safety Measures.
Chapter 6
Environmental Engineering: Environmental Pollution, Environmental Acts and Regulations, Functional Concepts of Ecology, Basics of Species, Biodiversity, Ecosystem, Hydrological Cycle; Chemical Cycles: Carbon, Nitrogen & Phosphorus; Energy Flow in Ecosystems.
Water Pollution: Water Quality standards, Introduction to Treatment & Disposal of Waste Water. Reuse and Saving of Water, Rain Water Harvesting. Solid Waste Management: Classification of Solid Waste, Collection, Transportation and Disposal of Solid. Recycling of Solid Waste: Energy Recovery, Sanitary Landfill, On-Site Sanitation. Air & Noise Pollution: Primary and Secondary air pollutants, Harmful effects of Air Pollution, Control of Air Pollution. . Noise Pollution Harmful Effects of noise pollution, control of noise pollution, Global warming & Climate Change, Ozone depletion, Greenhouse effect
Text Books:
1. Palancharmy, Basic Civil Engineering, McGraw Hill publishers.
2. Satheesh Gopi, Basic Civil Engineering, Pearson Publishers.
3. Ketki Rangwala Dalal, Essentials of Civil Engineering, Charotar Publishing House.
4. BCP, Surveying volume 1
it describes the bony anatomy including the femoral head , acetabulum, labrum . also discusses the capsule , ligaments . muscle that act on the hip joint and the range of motion are outlined. factors affecting hip joint stability and weight transmission through the joint are summarized.
How to Manage Your Lost Opportunities in Odoo 17 CRMCeline George
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LAND USE LAND COVER AND NDVI OF MIRZAPUR DISTRICT, UPRAHUL
This Dissertation explores the particular circumstances of Mirzapur, a region located in the
core of India. Mirzapur, with its varied terrains and abundant biodiversity, offers an optimal
environment for investigating the changes in vegetation cover dynamics. Our study utilizes
advanced technologies such as GIS (Geographic Information Systems) and Remote sensing to
analyze the transformations that have taken place over the course of a decade.
The complex relationship between human activities and the environment has been the focus
of extensive research and worry. As the global community grapples with swift urbanization,
population expansion, and economic progress, the effects on natural ecosystems are becoming
more evident. A crucial element of this impact is the alteration of vegetation cover, which plays a
significant role in maintaining the ecological equilibrium of our planet.Land serves as the foundation for all human activities and provides the necessary materials for
these activities. As the most crucial natural resource, its utilization by humans results in different
'Land uses,' which are determined by both human activities and the physical characteristics of the
land.
The utilization of land is impacted by human needs and environmental factors. In countries
like India, rapid population growth and the emphasis on extensive resource exploitation can lead
to significant land degradation, adversely affecting the region's land cover.
Therefore, human intervention has significantly influenced land use patterns over many
centuries, evolving its structure over time and space. In the present era, these changes have
accelerated due to factors such as agriculture and urbanization. Information regarding land use and
cover is essential for various planning and management tasks related to the Earth's surface,
providing crucial environmental data for scientific, resource management, policy purposes, and
diverse human activities.
Accurate understanding of land use and cover is imperative for the development planning
of any area. Consequently, a wide range of professionals, including earth system scientists, land
and water managers, and urban planners, are interested in obtaining data on land use and cover
changes, conversion trends, and other related patterns. The spatial dimensions of land use and
cover support policymakers and scientists in making well-informed decisions, as alterations in
these patterns indicate shifts in economic and social conditions. Monitoring such changes with the
help of Advanced technologies like Remote Sensing and Geographic Information Systems is
crucial for coordinated efforts across different administrative levels. Advanced technologies like
Remote Sensing and Geographic Information Systems
9
Changes in vegetation cover refer to variations in the distribution, composition, and overall
structure of plant communities across different temporal and spatial scales. These changes can
occur natural.
ISO/IEC 27001, ISO/IEC 42001, and GDPR: Best Practices for Implementation and...PECB
Denis is a dynamic and results-driven Chief Information Officer (CIO) with a distinguished career spanning information systems analysis and technical project management. With a proven track record of spearheading the design and delivery of cutting-edge Information Management solutions, he has consistently elevated business operations, streamlined reporting functions, and maximized process efficiency.
Certified as an ISO/IEC 27001: Information Security Management Systems (ISMS) Lead Implementer, Data Protection Officer, and Cyber Risks Analyst, Denis brings a heightened focus on data security, privacy, and cyber resilience to every endeavor.
His expertise extends across a diverse spectrum of reporting, database, and web development applications, underpinned by an exceptional grasp of data storage and virtualization technologies. His proficiency in application testing, database administration, and data cleansing ensures seamless execution of complex projects.
What sets Denis apart is his comprehensive understanding of Business and Systems Analysis technologies, honed through involvement in all phases of the Software Development Lifecycle (SDLC). From meticulous requirements gathering to precise analysis, innovative design, rigorous development, thorough testing, and successful implementation, he has consistently delivered exceptional results.
Throughout his career, he has taken on multifaceted roles, from leading technical project management teams to owning solutions that drive operational excellence. His conscientious and proactive approach is unwavering, whether he is working independently or collaboratively within a team. His ability to connect with colleagues on a personal level underscores his commitment to fostering a harmonious and productive workplace environment.
Date: May 29, 2024
Tags: Information Security, ISO/IEC 27001, ISO/IEC 42001, Artificial Intelligence, GDPR
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ISO/IEC 27001, ISO/IEC 42001, and GDPR: Best Practices for Implementation and...
A brief summary of my scientific contribution
1. My Computational Science Research
18 July 2014
Nol Chindapol, PhD Candidate
Section Computational Science
University of Amsterdam
Science Park 904, C3156
1098 XH Amsterdam
2. About Me
Mathematics &
Computer
Engineering
backgrounds
Passion in
Computational
science
3. Research Projects
Flow & Morphological Plasticity of Coral
Growth
Re-Modelling of Purkinje Cells Forest
4. Research questions
Is morphological plasticity the emergent property of the
external stressors induced by flow constraint to the sessile
organisms?
What is the interaction between those constraints and
intrinsic property of the organism that leads to self-generation
property of the growth forms?
How to quantify plastic response relevant to such
constraints?
5. Accretive growth model is coupled with FEM
modelling software (COMSOL) in order to
investigate the plasticity of the resulting growth
forms under uni-directional & bi-directional flow
(Tali et al. 2011)
Data Acquisition
6. Unidirectional Flow & Accretive Growth
Model
Nutrient
Injection
C = 1 mol/m3
Object and
Ground = Sink;
C = 0
Schematic diagram of the simulation (A) A spherical objected represents a simulated object in a first
growth step. (B) A simulation phase involves solving the Navier-Stokes equations and the Advection-
Diffusion equation. (C) Simulated growth form: the accretive growth process generates new growth
layers on top of the previous one.
7. Bidirectional Flow & Symmetry
perseverance Hypotheses
Schematic diagram of the bi-directional flow simulation coupled with the accretive growth model: (a)
initialization phase, (b) the simulation phase consists of two subsequence flow simulation steps. . (c) The
solutions of the nutrient transport are acquired and translocated on the surface of the simulated corals. The
next growth layer is built on top of the previous one by the local growth function
8. Advance Morphometric
Morphometric traits used in our quantitative analysis; (a) local morphometric traits (LMT) are
defined as local traits that are not associated with directional bias e.g. branch spacing (br_spacing),
branch angle (br_angle), ground angle (g_angle), and diameter of branches (da, db and dc) whereas
(b) symmetric-oriented traits (SOT) are those associated with directional bias (h_angle, v_angle, and
spd_angle) i.e. requiring the reference axis.
9. Bifurcations in nature are locally flat –
using data from Neurons & Corals
We do not touch upon this.
Yihawa et al. 2012
10. Morphospace of the flow-induced forms
An overview of the morphospace showing the transition from compact colony to thin branching form
by means of intrinsic model parameter n, while exposed to the flow condition with increasing Pe
number (i.e. decreasing diffusivity D). Red arrows indicate directional variation of flow. . (a) In silico corals
group 1 (b) In silico corals group 2(c) In silico corals group 3
11. Unpublished Work in Turbulent
Flow Simulation
Solved high Reynolds number flow by
using the one equation Spalart-
Allmaras turbulent model, and coupled
with growth model.
12. Flow & Morphological Plasticity of Coral Growth
Re-Modelling of Purkinje Cells Forest
13. Research Questions
How neuron’s complex morphology is created during nervous
development, and eventually leads to the development of
neuron forest.
How the interaction of genes mediates dendrite self-avoidance by
means of repulsive signal – discriminates self/non self.
The role of traveling waves in Purkinje cells during early
developmental stage and their significance in cortical microcircuit
wiring.
14. Dendritic infrastructure
We simulate the
growing micro tubes
i.e. the mechanic
property (e.g.
contact-mediated) is
reduced to a non-
volumetric
abstraction.
With VTKLines and
Tube Filter
16. Branching and remodeling
definition
Let dendritic tree composes of a n number of
cell (n=0,…k), in which each cell constitutes of a
finite set Li (i=0,..m)of non-bifurcated line;
branching mechanism is the addition of cellk+1 to
a non-terminated cell k.
Branch
?
Re-
model?
; re-modeling, on the other hand denotes an
action of trimming terminal cell, by which the line
Lm is eliminated, or redefined.
A finite-element mesh was constructed by generating a simulation box with dimensions 60 cm in x and y direction and 40 cm in z direction (the height of the simulation box) . The spherical object with an initial diameter of 6 cm was then imported to the simulation box.