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.
Perturbing The Interactome: Multi-Omics And Personalized Methods For Network ...Marc Santolini
In this talk, I will describe several recently developed methods to study disease perturbations through the lens of network science. First I will present evidence that one can accurately predict perturbation patterns from the topology of biological networks, even when lacking measurements on the kinetic parameters governing the dynamics of these interactions. Using 87 biochemical networks with experimentally measured kinetic parameters, we show that a knowledge of the network topology offers 65% to 80% accuracy in predicting the impact of perturbations. In other words, we can use the increasingly accurate topological models to approximate perturbation patterns, bypassing expensive kinetic constant measurement. These results open new avenues in modeling drug action, and in identifying drug targets relying on the human interactome only.
Then, I will present a novel approach to identify the collective impact of miRNAs in disease. Instead of focusing on the magnitude of miRNA differential expression, here we address the secondary consequences for the interactome. We developed the Impact of Differential Expression Across Layers (IDEAL), a network-based algorithm to prioritize disease-relevant miRNAs based on the central role of their targets in the molecular interactome. This method was used in the context of asthmatic Th2 inflammation and identified five Th2-related miRNAs (mir27b, mir206, mir106b, mir203, and mir23b) whose antagonization led to a sharp reduction of the Th2 phenotype. This result offers novel approaches for therapeutic interventions.
Finally, I will present an investigation of the personalized gene expression responses when inducing hypertrophy and heart failure in 100+ strains of genetically distinct mice from the Hybrid Mouse Diversity Panel (HMDP). I will show that genes whose expression change significantly correlates with the severity of the disease are either up- or down-regulated across strains, and therefore missed by traditional population-wide analyses of differential gene expression. These uncovered personalised genes are enriched in human cardiac disease genes and form a dense co-regulated module strongly interacting with the cardiac hypertrophic signaling network in the human interactome, the set of molecular interactions in the cell. We validate our approach by showing that the knockdown of Hes1, predicted as a strong candidate, induces a dramatic reduction of hypertrophy by 80-90% in neonatal rat ventricular myocytes, demonstrating that individualized approaches are crucial to identify genes underlying complex diseases as well as to develop personalized therapies.
Perturbing The Interactome: Multi-Omics And Personalized Methods For Network ...Marc Santolini
In this talk, I will describe several recently developed methods to study disease perturbations through the lens of network science. First I will present evidence that one can accurately predict perturbation patterns from the topology of biological networks, even when lacking measurements on the kinetic parameters governing the dynamics of these interactions. Using 87 biochemical networks with experimentally measured kinetic parameters, we show that a knowledge of the network topology offers 65% to 80% accuracy in predicting the impact of perturbations. In other words, we can use the increasingly accurate topological models to approximate perturbation patterns, bypassing expensive kinetic constant measurement. These results open new avenues in modeling drug action, and in identifying drug targets relying on the human interactome only.
Then, I will present a novel approach to identify the collective impact of miRNAs in disease. Instead of focusing on the magnitude of miRNA differential expression, here we address the secondary consequences for the interactome. We developed the Impact of Differential Expression Across Layers (IDEAL), a network-based algorithm to prioritize disease-relevant miRNAs based on the central role of their targets in the molecular interactome. This method was used in the context of asthmatic Th2 inflammation and identified five Th2-related miRNAs (mir27b, mir206, mir106b, mir203, and mir23b) whose antagonization led to a sharp reduction of the Th2 phenotype. This result offers novel approaches for therapeutic interventions.
Finally, I will present an investigation of the personalized gene expression responses when inducing hypertrophy and heart failure in 100+ strains of genetically distinct mice from the Hybrid Mouse Diversity Panel (HMDP). I will show that genes whose expression change significantly correlates with the severity of the disease are either up- or down-regulated across strains, and therefore missed by traditional population-wide analyses of differential gene expression. These uncovered personalised genes are enriched in human cardiac disease genes and form a dense co-regulated module strongly interacting with the cardiac hypertrophic signaling network in the human interactome, the set of molecular interactions in the cell. We validate our approach by showing that the knockdown of Hes1, predicted as a strong candidate, induces a dramatic reduction of hypertrophy by 80-90% in neonatal rat ventricular myocytes, demonstrating that individualized approaches are crucial to identify genes underlying complex diseases as well as to develop personalized therapies.
Alejo Rodriguez-Fraticelli, from Dr Fernando Martin-Belmonte’s laboratory in the CBMSO in Spain, has recently published with co-workers a paper in the Journal of Cell Biology in which they describe their approach to epithelial cells morphogenesis and uncover the role of cell confinement on epithelial polarity via peripheral actin contractility. The team sheds light on a phenomenon that is crucial to understand the physiology of the organs, but also the mechanisms underlying the development and progression of agressive epithelial cancers.
Alejo Rodriguez-Fraticelli, from Dr Fernando Martin-Belmonte’s laboratory in the CBMSO in Spain, has recently published with co-workers a paper in the Journal of Cell Biology in which they describe their approach to epithelial cells morphogenesis and uncover the role of cell confinement on epithelial polarity via peripheral actin contractility. The team sheds light on a phenomenon that is crucial to understand the physiology of the organs, but also the mechanisms underlying the development and progression of agressive epithelial cancers.
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
A Multiset Rule Based Petri net Algorithm for the Synthesis and Secretary Pat...ijsc
Membrane computing is a branch of Natural computing aiming to abstract computing models from the structure and functioning of the living cell. A comprehensive introduction to membrane computing is meant to offer both computer scientists and non-computer scientists an up-to date overview of the field. In this paper, we consider a uniform way of treating objects and rules in P Systems with the help of Multiset rewriting rules. Here the synthesis and secretary pathway of glycoprotein in epithelial cells of small intestine is considered as an example. A natural and finite link is explored between Petri nets and membrane Computing. A Petri net (PN) algorithm combined with P Systems is implemented for the synthesis and secretary pathway of Glycoprotein. To capture the compartmentalization of P Systems, the Petri net is extended with localities and to show how to adopt the notion of a Petri net process accordingly. The algorithm uses symbolic representations of multisets of rules to efficiently generate all the regions associated with the membrane. In essence, this algorithm is built from transport route sharing a set of places modeling the availability of system resources. The algorithm when simulated shows a significant pathway of safe Petri nets.
A Multiset Rule Based Petri net Algorithm for the Synthesis and Secretary Pat...ijsc
Membrane computing is a branch of Natural computing aiming to abstract computing models from the structure and functioning of the living cell. A comprehensive introduction to membrane computing is meant to offer both computer scientists and non-computer scientists an up-to date overview of the field. In
this paper, we consider a uniform way of treating objects and rules in P Systems with the help of Multiset rewriting rules. Here the synthesis and secretary pathway of glycoprotein in epithelial cells of small intestine is considered as an example. A natural and finite link is explored between Petri nets and membrane Computing. A Petri net (PN) algorithm combined with P Systems is implemented for the synthesis and secretary pathway of Glycoprotein. To capture the compartmentalization of P Systems, the Petri net is extended with localities and to show how to adopt the notion of a Petri net process accordingly.
The algorithm uses symbolic representations of multisets of rules to efficiently generate all the regions associated with the membrane. In essence, this algorithm is built from transport route sharing a set of places modeling the availability of system resources. The algorithm when simulated shows a significant
pathway of safe Petri nets.
ADAPTIVE SEGMENTATION OF CELLS AND PARTICLES IN FLUORESCENT MICROSCOPE IMAGEJournal For Research
Understanding the mechanisms of cell motility and their regulation is an important challenge in biomedical research. The ability of cells to exert forces on their environment and alter their shape as they move is essential to various biological processes such as the immune response, embryonic development, or tumor genesis .Recent technological advances in con-focal fluorescence microscopy have given researchers the opportunity to investigate these complex processes in vivo. However, they also lead to a tremendous increase in the amount of image data acquired during the studies. Therefore, the analysis of time-lapse experiments relies increasingly on automated image processing techniques. Namely, there is a high demand for fast and robust methods to help biologists to quantitatively analyze time-lapse image data. The potential of the proposed tracking scheme and the advantages and disadvantages of both frameworks are demonstrated on 2-D and 3-D time-lapse series of rat adipose-derived mesenchymal stem cells and human lung squamous cell carcinoma cells, respectively. The crucial tasks are, in particular, segmenting, tracking, and evaluating movement tracks and morphological changes of cells, sub-cellular components and other particles.
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
Live cells respond to the changes of their physiological environment as well as to the mechanical stimuli occurring in and out of the cell body. It is known that cell directional motion is influenced by the substrate stiffness. A finite element modelling based on the tensegrity approach is used here to describe the biomechanical behavior of cells. The effects of substrate stiffness and prestress on strain energy of a cell are investigated by defining several substrate stiffness values and prestress values. Numerical simulations reveal that the internal elastic strain energy of the cell decreases as the substrate stiffness increases. As prestress of cell increases, the strain energy increases as well. The change of prestress value does not change behavior pattern of the strain energy: strain energy of a cell will decrease when substrate stiffness increases. These findings indicate that both cell prestress and substrate stiffness influence the cell directional movement.
MODELING CELL MOVEMENT ON A SUBSTRATE WITH VARIABLE RIGIDITYijbesjournal
Live cells respond to the changes of their physiological environment as well as to the mechanical stimuli occurring in and out of the cell body. It is known that cell directional motion is influenced by the substrate stiffness. A finite element modelling based on the tensegrity approach is used here to describe the
biomechanical behavior of cells. The effects of substrate stiffness and prestress on strain energy of a cell are nvestigated by defining several substrate stiffness values and prestress values. Numerical simulations reveal that the internal elastic strain energy of the cell decreases as the substrate stiffness increases. As prestress of cell increases, the strain energy increases as well. The change of prestress value does not
change behavior pattern of the strain energy: strain energy of a cell will decrease when substrate stiffness increases. These findings indicate that both cell prestress and substrate stiffness influence the cell directional movement.
Large scale cell tracking using an approximated Sinkhorn algorithmParth Nandedkar
Cell tracking for a large scale (of over 1 million cells) has not yet been achievable within reasonable a time scope with current NN/RNN/Bi-RNN based methods. This individual research conducted by me at Osaka University, ISIR seeks to solve this problem using the Sinkhorn algorithm, and taking inspiration from the MPM method (Hayashida, 2020)
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
Empowering NextGen Mobility via Large Action Model Infrastructure (LAMI): pav...
20080516 Spontaneous separation of bi-stable biochemical systems
1. Spontaneous separation of bi-stable biochemical systems into spatial domains of opposite phases Johan Elf and Måns Ehrenberg Presented by Jonathan Blakes Computational Foundations of Nanoscience Journal Club 2008-05-16
lengthy abstract, disguises main point, that the supplementary material (which I will be going into) describes the next subvolume stochastic simulation method, this is implemented in MesoRD...
blood cells lines ODEs
David S. Goodsell
Rate matrix is sum of reactant rates (r) and diffusion rates (s), used to load the dice which is rolled to determine whether reaction or diffusion happens at this step.
Spontaneous domain separation requires that a localised part of the system jumps from an attractor in phase to an attractor out of phase with the surroundings. For this to happen, the size of the part of the system that jumps out of phase must be big enough so that it is not invaded by neighbouring molecules. At the same time, the size must be small enough so that the local escape from the original attractor does not take too long. It is only when there exists a local volume size for which invasion by diffusion takes a longer time than attractor escape, that spatial domains become sufficiently decoupled from their surroundings to allow for spontaneous domain separation. Accordingly, systems in tube-like or flat geometries display domain separation much more easily than do their spherical or cubic equivalents.
similar program from Luis Serrano’s laboratory, used Next Reaction Method (Gibson and Bruck) but switched to NSM because of overhead [quoth. MesoRD]