ReviewComputational and structural biotechnology journal2017
Scalability and Validation of Big Data Bioinformatics Software.
Review in Computational and structural biotechnology journal, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
24 citing papers in PubMed.
- The Computational Revolution in Natural Product Research: A Data-Driven Roadmap for Next-Generation Drug Development.Biology · 2026Review
- DGEAR: a web-based application for differential gene expression analysis and downstream functional insights.Functional & integrative genomics · 2025Article
- Formal verification of bioinformatics software using model checking and theorem proving.Briefings in bioinformatics · 2025Article
- Intronomics-MIP: a snakemake pipeline for analyzing multilocus intron polymorphisms in species identification and population genomics.BMC research notes · 2025Article
- Galaxy as a gateway to bioinformatics: Multi-Interface Galaxy Hands-on Training Suite (MIGHTS) for scRNA-seq.GigaScience · 2025Article
- Mpox Discourse on Twitter by Sexual Minority Men and Gender-Diverse Individuals: Infodemiological Study Using BERTopic.JMIR public health and surveillance · 2024Article
- To metabolomics and beyond: a technological portfolio to investigate cancer metabolism.Signal transduction and targeted therapy · 2023Review
- Assessing and assuring interoperability of a genomics file format.Bioinformatics (Oxford, England) · 2022Article
- Developing a real-world database for oncology: a descriptive analysis of breast cancer in Argentina.Ecancermedicalscience · 2022Article
- Improving bioinformatics software quality through incorporation of software engineering practices.PeerJ. Computer science · 2022Article
- Reproducible, scalable, and shareable analysis pipelines with bioinformatics workflow managers.Nature methods · 2021Review
- Performance and scaling behavior of bioinformatic applications in virtualization environments to create awareness for the efficient use of compute resources.PLoS computational biology · 2021Article
- Short loop functional commonality identified in leukaemia proteome highlights crucial protein sub-networks.NAR genomics and bioinformatics · 2021Article
- Biomedical Image Classification in a Big Data Architecture Using Machine Learning Algorithms.Journal of healthcare engineering · 2021Review
- Hybrid modelling for stroke care: Review and suggestions of new approaches for risk assessment and simulation of scenarios.NeuroImage. Clinical · 2021Review
- Article
- Bioinformatic analysis of subfamily-specific regions in 3D-structures of homologs to study functional diversity and conformational plasticity in protein superfamilies.Computational and structural biotechnology journal · 2021Article
- Computational Identification and Characterization of New microRNAs in Human Platelets Stored in a Blood Bank.Biomolecules · 2020Article
- AutoTuner: High Fidelity and Robust Parameter Selection for Metabolomics Data Processing.Analytical chemistry · 2020Article
- Metabolomics technology and bioinformatics for precision medicine.Briefings in bioinformatics · 2019Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This review examines two important aspects that are central to modern big data bioinformatics analysis - software scalability and validity. We argue that not only are the issues of scalability and validation common to all big data bioinformatics analyses, they can be tackled by conceptually related methodological approaches, namely divide-and-conquer (scalability) and multiple executions (validation). Scalability is defined as the ability for a program to scale based on workload. It has always been an important consideration when developing bioinformatics algorithms and programs. Nonetheless the surge of volume and variety of biological and biomedical data has posed new challenges. We discuss how modern cloud computing and big data programming frameworks such as MapReduce and Spark are being used to effectively implement divide-and-conquer in a distributed computing environment. Validation of software is another important issue in big data bioinformatics that is often ignored. Software validation is the process of determining whether the program under test fulfils the task for which it was designed. Determining the correctness of the computational output of big data bioinformatics software is especially difficult due to the large input space and complex algorithms involved. We discuss how state-of-the-art software testing techniques that are based on the idea of multiple executions, such as metamorphic testing, can be used to implement an effective bioinformatics quality assurance strategy. We hope this review will raise awareness of these critical issues in bioinformatics.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.