Data Science and Big Data in Biology, Physical Science and Engineering—3rd Edition
A special issue of Technologies (ISSN 2227-7080). This special issue belongs to the section "Information and Communication Technologies".
Deadline for manuscript submissions: 30 November 2026 | Viewed by 90
Special Issue Editor
Interests: data science; big data; machine learning; deep learning; artificial intelligence (AI); cybersecurity; software engineering
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Big Data analysis is one of the most contemporary areas of development and research in today's world. Tremendous amounts of data are generated daily from digital technologies and modern information systems, including cloud computing and Internet of Things (IoT) devices. Analysis of these enormous amounts of data has become a crucial need and requires a lot of effort to extract valuable knowledge for decision-making, which in turn will help in both academia and industry.
Big Data and Data Science have appeared due to the significant need for generating, storing, organising, and processing immense amounts of data. Data Scientists strive to utilize Artificial Intelligence (AI) and Machine Learning (ML) approaches and models, enabling computers to detect and identify the data's meaning and detect patterns more quickly, efficiently, and reliably than humans.
The goal of this Special Issue is to explore and discuss various principles, tools, and models in the context of Data Science, as well as diverse and varied concepts and techniques in Big Data, including those from Biology, Chemistry, Biomedical Engineering, Physics, Mathematics, and other areas that utilize Big Data.
Dr. Mohammed Mahmoud
Guest Editor
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Technologies is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- data science
- big data
- machine learning
- deep learning
- artificial intelligence
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