scholarly journals PECAn, a pipeline for image processing and statistical analysis of complex mosaic 3D tissues

2021 ◽  
Author(s):  
Michael E Baumgartner ◽  
Paul F Langton ◽  
Alex Mastrogiannopoulos ◽  
Remi Logeay ◽  
Eugenia Piddini
Keyword(s):  
Image Processing ◽  
Statistical Analysis ◽  
Statistical Data ◽  
Microscopic Analysis ◽  
Statistical Regression ◽  
Sample Analysis ◽  
Statistical Data Analysis ◽  
Cell Competition ◽  
3D Images ◽  
Spatial Anisotropy

Investigating organ biology requires sophisticated methodologies to induce genetically distinct clones within a tissue. Microscopic analysis of such samples produces information-rich 3D images. However, the 3D nature and spatial anisotropy of clones makes sample analysis challenging and slow and limits the amount of information that can be extracted manually. Here we have developed a pipeline for image processing and statistical data analysis which automatically extracts sophisticated parameters from complex multi-genotype 3D images. The pipeline includes data handling, machine-learning-enabled segmentation, multivariant statistical analysis, and graph generation. This enables researchers to run rigorous analyses on images and videos at scale and in a fraction of the time, without requiring programming skills. We demonstrate the power of this pipeline by applying it to the study of Minute cell competition. We find an unappreciated sexual dimorphism in Minute competition and identify, by statistical regression analysis, tissue parameters that model and predict competitive death.

scholarly journals Monitoring High Throughput Distributed System using Statistical Data Analysis

2020 ◽  
Vol 8 (6) ◽  
pp. 4590-4596
Keyword(s):  
Time Series ◽  
Statistical Analysis ◽  
Distributed System ◽  
High Throughput ◽  
Statistical Data ◽  
Time Interval ◽  
Statistical Data Analysis ◽  
Cloud Data ◽  
Data Pipeline ◽  
Cloud Data Centers

Monitoring high throughput distributed system by using a statistical analysis of the “historical time series” of an Instrumentation Data”. “The Pipeline has been made to process the information which can be otherwise called data pipeline, is a lot of information handling components associated in arrangement, where yield of one component is the contribution of the next one”. Several codes are giving different visualization for statistical analysis of data. “Network and Cloud Data Centers” generate a lot of data every second; this data can be gathered as period arrangement information. A timeseries is a grouping taken at progressive similarly dispersed focuses in time that implies at a particular time interval to a particular time, the estimations of explicit information that was taken is known as information of a time-series. “This time-series information can be gathered utilizing framework measurements like CPU, Memory, and Disk utilization”. The TICK and ELK Stack is abbreviation for a foundation of open source instruments worked “to make collection, storage, graphing, and alerting” on time arrangement data incredibly easy. As an information collector, using Telegraf, “for storing and analyzing” information and the time-series database InfluxDB and Elasticsearch. For plotting and visualizing used Grafana and Kibana. Watchman is utilized for alert refinement and once system metrics usage exceeds the specified threshold, the alert is generated and sends it to the Telegram.

scholarly journals Statistical Analysis of NMR Metabolic Fingerprints: Established Methods and Recent Advances

Metabolites ◽  
2018 ◽  
Vol 8 (3) ◽  
pp. 47 ◽  
Author(s):  
Helena Zacharias ◽  
Michael Altenbuchinger ◽  
Wolfram Gronwald
Keyword(s):  
Data Analysis ◽  
Statistical Analysis ◽  
Statistical Data ◽  
State Of The Art ◽  
Data Normalization ◽  
Statistical Data Analysis ◽  
Metabolomics Data ◽  
Pros And Cons ◽  
Zero Sum

In this review, we summarize established and recent bioinformatic and statistical methods for the analysis of NMR-based metabolomics. Data analysis of NMR metabolic fingerprints exhibits several challenges, including unwanted biases, high dimensionality, and typically low sample numbers. Common analysis tasks comprise the identification of differential metabolites and the classification of specimens. However, analysis results strongly depend on the preprocessing of the data, and there is no consensus yet on how to remove unwanted biases and experimental variance prior to statistical analysis. Here, we first review established and new preprocessing protocols and illustrate their pros and cons, including different data normalizations and transformations. Second, we give a brief overview of state-of-the-art statistical analysis in NMR-based metabolomics. Finally, we discuss a recent development in statistical data analysis, where data normalization becomes obsolete. This method, called zero-sum regression, builds metabolite signatures whose estimation as well as predictions are independent of prior normalization.

Knowledge-Based Decision Support for Diagnosis and Therapy: On the Multiple Usability of Patient Data

1989 ◽  
Vol 28 (02) ◽  
pp. 69-77 ◽  
Author(s):  
R. Haux
Keyword(s):  
Expert Systems ◽  
Statistical Data ◽  
Patient Data ◽  
Attribute Selection ◽  
Patient Specific ◽  
Statistical Data Analysis ◽  
Inference Mechanism ◽  
Diagnosis And Therapy ◽  
Knowledge Based ◽  
Clinical Registries

Abstract:Expert systems in medicine are frequently restricted to assisting the physician to derive a patient-specific diagnosis and therapy proposal. In many cases, however, there is a clinical need to use these patient data for other purposes as well. The intention of this paper is to show how and to what extent patient data in expert systems can additionally be used to create clinical registries and for statistical data analysis. At first, the pitfalls of goal-oriented mechanisms for the multiple usability of data are shown by means of an example. Then a data acquisition and inference mechanism is proposed, which includes a procedure for controlling selection bias, the so-called knowledge-based attribute selection. The functional view and the architectural view of expert systems suitable for the multiple usability of patient data is outlined in general and then by means of an application example. Finally, the ideas presented are discussed and compared with related approaches.

Market of Insurance in Russia: Major Tendencies and Problems of Development

2006 ◽  
pp. 115-127
Author(s):  
T Natkhov
Keyword(s):  
Data Analysis ◽  
Statistical Data ◽  
Statistical Data Analysis ◽  
Medium Term ◽  
Insurance Sector ◽  
Different Types ◽  
Basic Characteristics

The article considers recent tendencies in the development of the market of insurance in Russia. On the basis of statistical data analysis the most urgent problems of the insurance sector are formulated. Basic characteristics of different types of insurance are revealed, and measures on perfection of the insurance institution in the medium term are proposed.

Detection of Leukemia Using Image Processing

2018 ◽  
Vol 8 (4) ◽  
pp. 61
Author(s):  
A. Sivasangari ◽  
G. Sasikumar
Keyword(s):  
Image Processing ◽  
Statistical Analysis ◽  
Early Detection ◽  
Visual Inspection ◽  
Causes Of Death ◽  
Cure Rate ◽  
Blood Disorders ◽  
Detection And Diagnosis ◽  
The Moment ◽  
Early Detection And Diagnosis

Leukemia   disease   is one   of    the   leading   causes   of death   among   human. Its  cure  rate and  prognosis   depends   mainly   on  the  early  detection   and  diagnosis  of   the  disease. At  the  moment, identification  of  blood  disorders  is  through   visual  inspection  of  microscopic  images  by  examining  changes  like  texture, geometry, colour  and   statistical  analysis  of  images . This  project  aims  to  preliminary  of  developing  a  detection  of  leukemia  types  using   microscopic  blood  sample using MATLAB. Images  are  used  as  they  are  cheap  and  do  not  expensive  for testing  and  lab  equipment.

Visual Merchandising and Customers’ Impulse Buying Behavior: A Case of a Fashion Specialty Store

2020 ◽  
Vol 4 (1) ◽  
pp. 1
Author(s):  
Hadijah Iberahim ◽  
Nur Amira Zureena Zulkurnain ◽  
Raja Najwa Syamim Raja Ainal Shah ◽  
Siti Quraisyiah Rosli
Keyword(s):  
Adverse Effect ◽  
Statistical Data ◽  
Impulse Buying ◽  
Kuala Lumpur ◽  
Statistical Data Analysis ◽  
Buying Behavior ◽  
Specialty Store ◽  
Research Outcome ◽  
Five Elements ◽  
Visual Merchandising

Visual merchandising is an extremely important element as the first visual cue that affects buying behavior of customers. This study aims to identify determinants of visual merchandising that influence customers’ impulse buying behavior. This study focuses on five elements of visual merchandising which are window display, mannequin display, floor merchandising, promotional signage and lighting. Investigation was conducted at a popular fashion specialty store in Kuala Lumpur, Malaysia. A total of 150 customers' feedback was collected. Results of statistical data analysis show that three out of five visual merchandising elements are important in influencing the customers’ impulse buying behavior. Window display, mannequin display and promotional signage are positively related and identified as determinants of effective visual merchandising for impulse buying decision at the women fashion specialty store. The research outcome extends understanding on the adverse effect of visual merchandising on customers’ behavior.

BANK SPÓŁDZIELCZY (COOPERATIVE BANK) AS A GUARANTOR OF THE STABILISATION OF THE LOCAL FINANCIAL SYSTEM1

2019 ◽  
pp. 173-179
Author(s):  
Andrzej Pawlik
Keyword(s):  
Data Analysis ◽  
Banking Sector ◽  
Statistical Data ◽  
Local Development ◽  
Banking System ◽  
Analysis Method ◽  
Statistical Data Analysis ◽  
Data Analysis Method ◽  
Strong Position ◽  
Cooperative Banks

Urgency of the research. One of the most essential sources of supporting regional and local development is the banking system. Target setting. The study presented describes cooperative banking, represented by Bank Polskiej Spółdzielczości S.A. and Bank Spółdzielczy w Kielcach. The use of the statistical data analysis method allowed to demonstrate the strong position of cooperative banking in the market, fostering regional and local development. Actual scientific researches and issues analysis. The foundations for the modern cooperative banking sector were laid by cooperative financial organisations functioning more than 150 years ago [Pawlik, 2017, s. 152]. Its history is connected with difficulties faced in the period of partitions, work at the foundations after the end of World War I and Poland’s regaining its national independence. Uninvestigated parts of general matters defining. At present, cooperative banking functions as a result of the adoption by the Sejm of the Republic of Poland on 7 December 2000 of the act on the functioning of cooperative banks, their associations and associating banks, which ensured new legal conditions for the functioning of the sector2. The research objective. The article formulates the hypothesis that nowadays activities of cooperative banks will contribute to regional and local development. The statement of basic materials. One of the most essential sources of supporting regional and local development is the banking system. This system can guarantee the stabilisation of the local financial system. By supporting the development of regional and local entrepreneurship through loans, investment activities of the banks and financial and investment consulting, it will determine the identity of the region concerned. Conclusions. The use of the statistical data analysis method allowed to demonstrate the strong position of cooperative banking in the market, fostering regional and local development.

Sign in / Sign up

Export Citation Format

Share Document