This document discusses analyzing the variance of multiplexed qPCR systems as a whole rather than individually. It provides examples of calculating variance based on the frequency of particles in a matrix for a multiplex system. This %CV value for the whole system provides clarity on whether to accept or reject sample results, with an acceptance threshold of 10% CV compared to controls. Analyzing the system as a single unit accounts for interactions between targets that analyzing them individually does not.
Measuring Comparability of Conformation, Heterogeneity and Aggregation with C...KBI Biopharma
"Measuring Comparability of Conformation, Heterogeneity, and Aggregation with Circular Dichroism and Analytical Ultracentrifugation", invited talk, State of the Art Methods for the Characterization of Biological Products and Assessment of Comparability, NIH, June 2003
Application of MicroTester for detection of low microbial contaminationOlivér Reichart
Advantades of the redox method in the evaluation of membrane filtration:
* The time requirement of the redox-potential technique is significantly lower than that of the classical nutrient methods.
* While the classical methods use only 1 membrane in 1 Petri dish the redox-potential method makes possible to evaluate even 5 or more filters in one test cell. That means not only a 5 times lower detection limit of microbes but results in a remarkable cost reduction as well.
Measuring Comparability of Conformation, Heterogeneity and Aggregation with C...KBI Biopharma
"Measuring Comparability of Conformation, Heterogeneity, and Aggregation with Circular Dichroism and Analytical Ultracentrifugation", invited talk, State of the Art Methods for the Characterization of Biological Products and Assessment of Comparability, NIH, June 2003
Application of MicroTester for detection of low microbial contaminationOlivér Reichart
Advantades of the redox method in the evaluation of membrane filtration:
* The time requirement of the redox-potential technique is significantly lower than that of the classical nutrient methods.
* While the classical methods use only 1 membrane in 1 Petri dish the redox-potential method makes possible to evaluate even 5 or more filters in one test cell. That means not only a 5 times lower detection limit of microbes but results in a remarkable cost reduction as well.
An Illustration from Heart Rate Variability Data
I have made an attempt to make calcification of different activities from Hear Rate Variability (HRV) data. I have also used model comparison here. Mostly it is graphics, but I will try to add some more text in future.
Quantification of a Novel Peptide, CPT31 in Rat and Monkey Plasma by LC-MSCovance
ASMS 2019 -- CPT31, a novel D-peptide, is being investigated in the treatment and prevention of HIV by inhibiting the viral entry of HIV. To evaluate the properties of CPT31, an accurate highly reproducible method to quantitate CPT31 in plasma was required. To this end, a robust LC-MS assay for the quantification of CPT31 in rat and monkey plasma samples is reported here. The method follows extraction and clean-up of two plasma matrices, encompasses a range of 90.0 to 45,000 ng/mL, and completes LC-MS analysis in 7.50 minutes.
Evolving Fuzzy System Applied to Battery Charge Capacity Prediction for Faul...Murilo Camargos
This paper addresses the use of data-driven evolving techniques applied to fault prognostics in Li-ion batteries. In such problems, accurate predictions of multiple steps ahead are essential for the Remaining Useful Life (RUL) estimation of a given asset. The fault prognostics' solutions must be able to model the typical nonlinear behavior of the degradation processes of these assets, and be adaptable to each unit's particularities. In this context, the Evolving Fuzzy Systems (EFS) are models capable of representing such behaviors, in addition of being able to deal with non-stationary behavior, also present in these problems. Moreover, a methodology to recursively track the model's estimation error is presented as a way to quantify uncertainties that are propagated in the long-term predictions. The well-established NASA's Li-ion batteries data set is used to evaluate the models. The experiments indicate that generic EFS can take advantage of both historical and stream data to estimate the RUL and its uncertainty.
In-silico structure activity relationship study of toxicity endpoints by QSAR...Kamel Mansouri
Several thousand chemicals were tested in hundreds of toxicity-related in-vitro high-throughput screening (HTS)
bioassays through the EPA’s ToxCast and Tox21 projects. However, this chemical set only covers a portion of the chemical
space of interest for environmental risk assessment, leading to a need to fill data gaps with other methods. A cost effective
and reliable approach to fullfill this task is to build quantitative structure-activity relationships (QSARs).
In this work, a subset of 1877 chemicals from ToxCast were used to build QSAR models. These models will be applied
to predict values for multiple ToxCast assays in a larger environmental database of ~30K chemical structures.
Based on a clustering study by Sipes et al. (2013), the initial molecular targets of this effort consisted of a set of 18
NovaScreen G-protein coupled receptor (GPCR) assays. These assays are part of the aminergic category that showed the
highest number of actives within the ToxCast portfolio. Classification methods including SOM, SVM, PLSDA and kNN, were
tested. These methods were coupled to variable selection techniques such as genetic algorithms that were applied in order
to select the best representative molecular descriptors based on statistical fitness functions. The obtained models were
validated and their prediction ability measured. The models that showed good results will be applied within the limits of
their established chemical space defined by the applicability domain.
Ion Torrent™ semiconductor sequencing, combined with Ion AmpliSeq™ technology, provides simultaneous identification of copy number variants (CNVs), single nucleotide variants (SNVs), and small insertions and deletions (indels) from a research sample by means of a single integrated workflow. 100% of assayed CNV regions (n=34) were detected using a reference set of 31 samples with known chromosomal aberrations. Low-pass whole-genome sequencing data, with approximately 0.01x read coverage, allowed the rapid ≤10 hour analysis of aneuploidies from research samples with extremely low initial input DNA amounts—even from a single cell. Using a control set of 10 samples with known chromosomal aberrations, 100% of the copy number changes were found, ranging from gains or losses of whole chromosomes to subchromosomal alterations tens of megabases (Mb) in size. The Ion PGM™ System minimizes the high cost and complexity of next-generation sequencing and, with Ion Reporter™ Software, facilitates user-defined CNV and aneuploidy detection, with three sensitivity options so that copy number analysis workflows can be tuned to achieve desired levels of sensitivity and specificity.
Multicopy reference assay (MRef) — a superior normalizer of sample input in D...QIAGEN
Copy number variations (CNVs) and alterations (CNAs) are a source of genetic diversity in humans and are often pathogenic. Numerous CNVs and CNAs are being identified with various genome analysis platforms, including array comparative genomic hybridization (aCGH), single nucleotide polymorphism (SNP) genotyping platforms, and next-generation sequencing. Independent verification of copy number changes is a critical step. Quantitative real-time PCR (qPCR) is a classic method to verify microarray copy number findings. Traditional copy number assays that use qPCR typically rely on a putative single-copy gene reference assay (e.g., RNase P or TERT) to normalize the DNA input for downstream ΔΔCT-based copy number calculation for comparison to a reference genome. When applied to cancer samples, these single-copy reference assays may no longer be a reliable indicator of DNA input due to the presence of complex chromosome composition (both in chromosome number and structure). To meet the need for an accurate DNA input normalizer, especially for heterogeneous tumor samples, QIAGEN developed a multicopy reference (MRef) assay for real-time PCR copy number analysis. This assay, in conjunction with QIAGEN’s greater than 10 million genomewide copy number assays and pathway- and disease-focused copy number PCR arrays (Figure 1), provides a successful solution for copy number analysis. This article will address the assay design considerations, development, and performance of this multicopy reference (MRef) assay.
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
An Illustration from Heart Rate Variability Data
I have made an attempt to make calcification of different activities from Hear Rate Variability (HRV) data. I have also used model comparison here. Mostly it is graphics, but I will try to add some more text in future.
Quantification of a Novel Peptide, CPT31 in Rat and Monkey Plasma by LC-MSCovance
ASMS 2019 -- CPT31, a novel D-peptide, is being investigated in the treatment and prevention of HIV by inhibiting the viral entry of HIV. To evaluate the properties of CPT31, an accurate highly reproducible method to quantitate CPT31 in plasma was required. To this end, a robust LC-MS assay for the quantification of CPT31 in rat and monkey plasma samples is reported here. The method follows extraction and clean-up of two plasma matrices, encompasses a range of 90.0 to 45,000 ng/mL, and completes LC-MS analysis in 7.50 minutes.
Evolving Fuzzy System Applied to Battery Charge Capacity Prediction for Faul...Murilo Camargos
This paper addresses the use of data-driven evolving techniques applied to fault prognostics in Li-ion batteries. In such problems, accurate predictions of multiple steps ahead are essential for the Remaining Useful Life (RUL) estimation of a given asset. The fault prognostics' solutions must be able to model the typical nonlinear behavior of the degradation processes of these assets, and be adaptable to each unit's particularities. In this context, the Evolving Fuzzy Systems (EFS) are models capable of representing such behaviors, in addition of being able to deal with non-stationary behavior, also present in these problems. Moreover, a methodology to recursively track the model's estimation error is presented as a way to quantify uncertainties that are propagated in the long-term predictions. The well-established NASA's Li-ion batteries data set is used to evaluate the models. The experiments indicate that generic EFS can take advantage of both historical and stream data to estimate the RUL and its uncertainty.
In-silico structure activity relationship study of toxicity endpoints by QSAR...Kamel Mansouri
Several thousand chemicals were tested in hundreds of toxicity-related in-vitro high-throughput screening (HTS)
bioassays through the EPA’s ToxCast and Tox21 projects. However, this chemical set only covers a portion of the chemical
space of interest for environmental risk assessment, leading to a need to fill data gaps with other methods. A cost effective
and reliable approach to fullfill this task is to build quantitative structure-activity relationships (QSARs).
In this work, a subset of 1877 chemicals from ToxCast were used to build QSAR models. These models will be applied
to predict values for multiple ToxCast assays in a larger environmental database of ~30K chemical structures.
Based on a clustering study by Sipes et al. (2013), the initial molecular targets of this effort consisted of a set of 18
NovaScreen G-protein coupled receptor (GPCR) assays. These assays are part of the aminergic category that showed the
highest number of actives within the ToxCast portfolio. Classification methods including SOM, SVM, PLSDA and kNN, were
tested. These methods were coupled to variable selection techniques such as genetic algorithms that were applied in order
to select the best representative molecular descriptors based on statistical fitness functions. The obtained models were
validated and their prediction ability measured. The models that showed good results will be applied within the limits of
their established chemical space defined by the applicability domain.
Ion Torrent™ semiconductor sequencing, combined with Ion AmpliSeq™ technology, provides simultaneous identification of copy number variants (CNVs), single nucleotide variants (SNVs), and small insertions and deletions (indels) from a research sample by means of a single integrated workflow. 100% of assayed CNV regions (n=34) were detected using a reference set of 31 samples with known chromosomal aberrations. Low-pass whole-genome sequencing data, with approximately 0.01x read coverage, allowed the rapid ≤10 hour analysis of aneuploidies from research samples with extremely low initial input DNA amounts—even from a single cell. Using a control set of 10 samples with known chromosomal aberrations, 100% of the copy number changes were found, ranging from gains or losses of whole chromosomes to subchromosomal alterations tens of megabases (Mb) in size. The Ion PGM™ System minimizes the high cost and complexity of next-generation sequencing and, with Ion Reporter™ Software, facilitates user-defined CNV and aneuploidy detection, with three sensitivity options so that copy number analysis workflows can be tuned to achieve desired levels of sensitivity and specificity.
Multicopy reference assay (MRef) — a superior normalizer of sample input in D...QIAGEN
Copy number variations (CNVs) and alterations (CNAs) are a source of genetic diversity in humans and are often pathogenic. Numerous CNVs and CNAs are being identified with various genome analysis platforms, including array comparative genomic hybridization (aCGH), single nucleotide polymorphism (SNP) genotyping platforms, and next-generation sequencing. Independent verification of copy number changes is a critical step. Quantitative real-time PCR (qPCR) is a classic method to verify microarray copy number findings. Traditional copy number assays that use qPCR typically rely on a putative single-copy gene reference assay (e.g., RNase P or TERT) to normalize the DNA input for downstream ΔΔCT-based copy number calculation for comparison to a reference genome. When applied to cancer samples, these single-copy reference assays may no longer be a reliable indicator of DNA input due to the presence of complex chromosome composition (both in chromosome number and structure). To meet the need for an accurate DNA input normalizer, especially for heterogeneous tumor samples, QIAGEN developed a multicopy reference (MRef) assay for real-time PCR copy number analysis. This assay, in conjunction with QIAGEN’s greater than 10 million genomewide copy number assays and pathway- and disease-focused copy number PCR arrays (Figure 1), provides a successful solution for copy number analysis. This article will address the assay design considerations, development, and performance of this multicopy reference (MRef) assay.
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
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.
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
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.
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
Generating a custom Ruby SDK for your web service or Rails API using Smithyg2nightmarescribd
Have you ever wanted a Ruby client API to communicate with your web service? Smithy is a protocol-agnostic language for defining services and SDKs. Smithy Ruby is an implementation of Smithy that generates a Ruby SDK using a Smithy model. In this talk, we will explore Smithy and Smithy Ruby to learn how to generate custom feature-rich SDKs that can communicate with any web service, such as a Rails JSON API.
Generating a custom Ruby SDK for your web service or Rails API using Smithy
A System Approach
1. Variance Analysis For Multiplexed
qPCR Samples: A System Approach
Designed by Geoffrey Dennis and
Concept Proofed by Hugo DiGiulio
2. Variance Analysis of Multiplexed
Systems: Individual vs. Whole
• Multiplexing ≥ 2 gene targets for quantitation in single
well format
• Typical basic analysis of individual amplisets includes
CV (RSD), CI, relevant t-test
• Comparison between systems can be done by ANCOVA,
t-test, χ test, etc.
• By use of dilution series, the multiplex can be set up as a
matrix and the system variance can be analyzed as a
single unit
– This is done by calculating a %CV based on frequency of
particles
– using %CV calculated by frequency of particles provides clarity
on the decision to accept or not accept the outcome of a sample
5. Example of Variance Analysis of System
as Whole: Accept or Reject?
• While 36% is typically
acceptable in c/mL for qPCR,
calculating %CV by using
frequency of particles in a
matrix may result in a need to
repeat the sample
• Observed acceptance tolerance
was at a maximum of 10% CV
compared to controls
Sample A Gene 1 Gene 2 Gene 3
Sample dilution 1 3.10E+09 3.30E+09 3.18E+09
Sample dilution 2 3.96E+09 3.17E+09 3.47E+09
17.4% 2.7% 6.1% %CV
Sample dilution 1 0.32 0.34 0.33
Sample dilution 2 0.37 0.30 0.33
0.7 0.7 0.7
0.0 0.0 0.0
5.5% %CV
Sample B Gene 1 Gene 2 Gene 3
Sample dilution 1 1.88E+09 2.07E+09 3.00E+09
Sample dilution 2 3.12E+09 3.48E+09 3.46E+09
35.0% 36.0% 10.1% %CV
Sample dilution 1 0.27 0.30 0.43
Sample dilution 2 0.31 0.35 0.34
0.6 0.7 0.7
0.0 -0.1 -0.1
12.7% %CV
Resulting
c/mL
Frequency of
Particles
Calculated
Lambdas
Resulting
c/mL
Frequency of
Particles
Calculated
Lambdas
6. Variance Analysis of a System as a Whole
• For each additional ampliset,
– %CV = (2+N additional sets)- Σ(λ1 + λ2)
∀± CV indicates direction of inconsistency in
system (but remember, since 2+N used, the
result indicates the inverse of the direction!)
7. Variance Analysis System Dynamics
-0.08
-0.06
-0.04
-0.02
0
0.02
0.04
0.06
0.08
0.1
0.12
0.6 0.62 0.64 0.66 0.68 0.7 0.72 0.74
Series1
Series2
Series3
Series4
Series 1 0.06
Series 2 0.13
Series 3 -0.02
Series 4 -0.18
System CV
The arrows show how signal changes are reflected with this analysis
11. Conclusion
• In conclusion, using %CV based on
matrices calculated by frequency of
particles provides clarity on the decision to
accept or not accept the outcome of a
sample
