Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Issues And Trends In Healthcare Delivery System

Issues And Trends In Healthcare Delivery System

The issues and trends in healthcare delivery are constantly changing. The COVID-19 pandemic is one recent issue that wreaked havoc on healthcare systems, causing a shortage of healthcare workers, high demand for medicines and supplies, and increased medical expenditure due to a lack of insurance. Other issues include rising healthcare costs and care fragmentation.
Cost Containment
Payment for healthcare services has historically promoted adoption of costly and often unnecessary or inefficient...

Hybridoma Technology

Hybridoma Technology

Hybridoma technology is used for the large-scale production of monoclonal antibodies. Monoclonal antibodies bind to only a single antigenic determinant or epitope. Such antibodies are used in research, diagnostics, and disease therapy. The hybridoma technology established in 1975 by Georges Köhler and Cesar Milstein was awarded the Nobel Prize in Medicine in 1984 for revolutionizing research and therapy.
Hybridoma Selection
Commonly used fusion techniques — electroporation, polyethylene glycol...

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

Pharmacokinetic models are mathematical constructs that represent and predict the time course of drug concentrations in the body, providing meaningful pharmacokinetic parameters. These models are categorized into compartment, physiological, and distributed parameter models.
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...

Model-Independent Approaches for Pharmacokinetic Data: Noncompartmental Analysis

Model-Independent Approaches for Pharmacokinetic Data: Noncompartmental Analysis

Noncompartmental analyses offer an alternative method for describing drug pharmacokinetics without relying on a specific compartmental model. In this approach, the drug's pharmacokinetics are assumed to be linear, with the terminal phase log-linear. This assumption allows for simplified analysis and interpretation of the drug's behavior in the body.
One important characteristic of noncompartmental analyses is that drug exposure increases proportionally with increasing doses. This relationship...

Model Approaches for Pharmacokinetic Data: Compartment Models

Model Approaches for Pharmacokinetic Data: Compartment Models

Compartmental analysis is a widely adopted approach to characterizing drug pharmacokinetics. It uses compartment models that conceptualize the body as a collection of reversibly communicating compartments, each representing a group of tissues exhibiting similar drug distribution characteristics. The movement rate of the drug between these compartments is typically described by first-order kinetics.
Two primary types of compartment models are recognized: mammillary and catenary. The more...

Health Information Technology and Healthcare Information System

Health Information Technology and Healthcare Information System

Health Information Technology (HIT)
Health Information Technology, commonly called HIT, integrates advanced information systems and technology in healthcare settings. Its primary functions include:

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

A universal 6iL/E4 culture system for deriving and maintaining embryonic stem cells across mammalian species.

Cell research·2026

Same author

From military to civilian nursing: A grounded theory of non-technical competence and the Four-C model.

Nurse education in practice·2026

Same author

Surrogate modeling of Cellular-Potts agent-based models as a segmentation task using the U-Net neural network architecture.

PLoS computational biology·2025

Same author

Generative diffusion model surrogates for mechanistic agent-based biological models.

Machine learning: science and technology·2025

Same author

Generative diffusion model surrogates for mechanistic agent-based biological models.

ArXiv·2025

Same author

Contemporary management of phyllodes tumours of the breast: recommendations from the UK Association of Breast Surgery.

The British journal of surgery·2025

Search research articles

Related Experiment Video

Updated: Jun 5, 2026

Leveraging CyVerse Resources for De Novo Comparative Transcriptomics of Underserved (Non-model) Organisms

Leveraging CyVerse Resources for De Novo Comparative Transcriptomics of Underserved (Non-model) Organisms

Published on: May 9, 2017

Hybrid cloud and cluster computing paradigms for life science applications.

Judy Qiu¹, Jaliya Ekanayake, Thilina Gunarathne

¹School of Informatics and Computing, Indiana University, Bloomington, IN 47405, USA. xqiu@indiana.edu

BMC Bioinformatics

|January 8, 2011

Summary

A hybrid approach combining cloud (MapReduce) and cluster (MPI) computing offers efficient data analysis. The open-source Twister Iterative MapReduce system provides a unified programming environment for scientific computing, particularly in life sciences.

More Related Videos

Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications

Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications

Published on: February 23, 2019

Related Experiment Videos

Last Updated: Jun 5, 2026

Leveraging CyVerse Resources for De Novo Comparative Transcriptomics of Underserved (Non-model) Organisms

Leveraging CyVerse Resources for De Novo Comparative Transcriptomics of Underserved (Non-model) Organisms

Published on: May 9, 2017

Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications

Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications

Published on: February 23, 2019

Area of Science:

Scientific computing
Data-intensive applications
Life sciences

Background:

Cloud computing and MapReduce are effective for parallel, data-intensive tasks.
MapReduce shows poor performance on iterative problems common in data mining and linear algebra.
Message Passing Interface (MPI) efficiently handles iterative computations on clusters.

Purpose of the Study:

To design and implement Twister, an open-source Iterative MapReduce system.
To evaluate a hybrid cloud (MapReduce) and cluster (MPI) computing environment.
To provide a uniform programming environment for scientific applications.

Main Methods:

Utilized commercial clouds (Amazon, Azure) and FutureGrid for comparisons.
Developed applications using MPI, MapReduce, and Twister.
Benchmarked Twister against Hadoop MapReduce and MPI.

Main Results:

Commercial cloud and traditional environments showed comparable performance for non-iterative tasks.
Hybrid approach links MapReduce with MPI for advanced data analysis.
Twister demonstrated competitive performance in information retrieval and life sciences applications.

Conclusions:

A hybrid cloud-MapReduce and cluster-MPI approach is suitable for production environments.
Twister offers a unified programming model for diverse scientific computing needs, especially in life sciences.