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...

Genomics

Genomics

Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...

Proteomics

Proteomics

A proteome is the entire set of proteins that a cell type produces. We can study proteomes using the knowledge of genomes because genes code for mRNAs, and the mRNAs encode proteins. Although mRNA analysis is a step in the right direction, not all mRNAs are translated into proteins.
Proteomics is the study of proteomes' function. It involves the large-scale systematic study of the proteome to denote the protein complement expressed by a genome. Scientist Mark Wilkins coined the term proteomics...

Statistical Software for Data Analysis and Clinical Trials

Statistical Software for Data Analysis and Clinical Trials

Statistical software is pivotal in data analysis and clinical trials by providing tools to analyze data, draw conclusions, and make predictions. These software packages range from simple data management applications to complex analytical platforms, supporting various statistical tests, models, and simulation techniques. Their significance lies in their ability to handle vast amounts of data with precision and efficiency, enabling researchers to validate hypotheses, identify trends, and make...

Protein Networks

Protein Networks

An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...

Next-generation Sequencing

Next-generation Sequencing

The first human genome sequencing project cost $2.7 billion and was declared complete in 2003, after 15 years of international cooperation and collaboration between several research teams and funding agencies. Today, with the advent of next-generation sequencing technologies, the cost and time of sequencing a human genome have dropped over 100 fold.
Next-Generation Sequencing Methods
Although all next-generation methods use different technologies, they all share a set of standard features.

You might also read

Related Articles

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

Sort by

Same author

Twelve-year trends in sex and age of patients with COPD and chronic respiratory failure undergoing pulmonary rehabilitation.

European journal of internal medicine·2026

Same author

Why almost all ML models for medicine are wrong-and what we need for evidence-based medical AI.

International journal of medical informatics·2026

Same author

Evaluating large language models for structuring cardiology reports: a real-world clinical study on patient subtyping and trial recruitment.

International journal of medical informatics·2026

Same author

ViTMARE - A Vision Transformer Pipeline for Anomaly Detection in 3D Brain MRI.

Studies in health technology and informatics·2026

Same author

Environmental Personal Exposure Clusters to Investigate Multiple Sclerosis and Amyotrophic Lateral Sclerosis Progression.

Studies in health technology and informatics·2026

Same author

Machine Learning Prediction of Growth Hormone Response in Children Non-Growth Hormone-Deficient Short Stature.

Studies in health technology and informatics·2026

Search research articles

Related Experiment Video

Updated: May 17, 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

Clinical Bioinformatics: challenges and opportunities.

Riccardo Bellazzi¹, Marco Masseroli, Shawn Murphy

¹Dipartimento di Ingegneria Industriale e dell'Informazione, Università di Pavia, Via Ferrata 1, 27100, Pavia, Italy. riccardo.bellazzi@unipv.it

BMC Bioinformatics

|October 26, 2012

Summary

Clinical Bioinformatics (CBI) leverages advanced ICT tools and data infrastructures to integrate "-omics" data with clinical information. Future efforts focus on data sharing standards and efficient search solutions for biomedical research advancements.

More Related Videos

Integration of Bioinformatics Approaches and Experimental Validations to Understand the Role of Notch Signaling in Ovarian Cancer

Integration of Bioinformatics Approaches and Experimental Validations to Understand the Role of Notch Signaling in Ovarian Cancer

Published on: January 12, 2020

Microbial Communities in Nature and Laboratory - Interview

Microbial Communities in Nature and Laboratory - Interview

Published on: May 28, 2007

Related Experiment Videos

Last Updated: May 17, 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

Integration of Bioinformatics Approaches and Experimental Validations to Understand the Role of Notch Signaling in Ovarian Cancer

Integration of Bioinformatics Approaches and Experimental Validations to Understand the Role of Notch Signaling in Ovarian Cancer

Published on: January 12, 2020

Microbial Communities in Nature and Laboratory - Interview

Microbial Communities in Nature and Laboratory - Interview

Published on: May 28, 2007

Area of Science:

Bioinformatics
Computational Biology
Health Informatics

Background:

The Network Tools and Applications in Biology (NETTAB) 2011 workshop focused on Information and Communication Technology (ICT) tools for Clinical Bioinformatics (CBI).
CBI integrates bioinformatics methods and tools for clinical applications, addressing the growing need for data analysis in healthcare.

Discussion:

Expert opinions highlight key challenges and opportunities in CBI, including data warehousing, ICT infrastructure development, and data sharing.
Emphasis is placed on establishing standards for phenotypic data sharing and developing novel search computing solutions.

Key Insights:

Essential design features for CBI-ICT infrastructure include data warehousing, modularity, flexibility, and open-source development.
Semantic interoperability and integrated search/retrieval of -omics data are crucial for effective CBI.

Outlook:

Ambitious goals in CBI are supported by high-throughput -omics technologies and increasing data storage/computational power.
CBI is poised to become a critical factor in advancing biomedical research through the integration of clinical and biological data.