Machine Learning and Bioinformatics in Human Health and Disease: 2nd Edition
A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Informatics".
Deadline for manuscript submissions: 31 December 2024 | Viewed by 45
Special Issue Editor
Interests: cardiology; epidemiology; virology; adipose tissue; metabolism; nutrition; data science; diabetes; renal disease; biomarker
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Machine learning and bioinformatics have emerged as powerful tools for analyzing complex biological data and driving advances in human health and disease research. These fields offer a range of techniques for learning from and making predictions based on biological data, including genetic sequencing data, protein structure data, and medical imaging data.
In the context of human health and disease, machine learning and bioinformatics can be used to identify biomarkers for diseases, predict treatment outcomes, and develop new therapies. For example, machine learning algorithms can be used to analyze large datasets of patient information and identify patterns and correlations that might be missed by human experts. Bioinformatics techniques can be utilized to analyze genomic data and identify genetic variations that may contribute to disease.
Machine learning and bioinformatics techniques can also be used to analyze medical images, such as MRIs and CT scans, to identify structural changes associated with disease or injury. This can enable earlier and more accurate diagnoses, as well as more personalized treatment plans tailored to the specific needs of each patient.
However, as is the case with any computational method, machine learning and bioinformatics techniques have their limitations and challenges. One challenge is the need for large amounts of high-quality data to train and validate the algorithms. Another challenge is the potential for overfitting, where the algorithms learn patterns specific to the training data that cannot be applied to new data.
Despite these challenges, the potential benefits of applying machine learning and bioinformatics techniques to human health and disease research are extensive. This Special Issue will provide a platform for researchers to share their latest findings, insights, and innovations in this rapidly evolving field.
Potential topics include, but are not limited to, the following:
- Machine learning approaches for identifying genetic risk factors for common diseases;
- Analysis of single-cell RNA sequencing data using bioinformatics and machine learning techniques;
- Machine learning for predicting drug interactions and side effects;
- Bioinformatics and machine learning for precision medicine in cancer treatment;
- Machine learning-based diagnosis of neurodegenerative diseases using neuroimaging data;
- Integrating multi-omics data using machine learning techniques for disease diagnosis and treatment;
- Development of predictive models for infectious disease outbreaks using machine learning and epidemiological data;
- Application of machine learning and deep learning techniques in medical image analysis for disease diagnosis and treatment planning;
- Identifying disease biomarkers using bioinformatics, deep learning, and machine learning approaches;
- Machine learning approaches for predicting patient outcomes and disease progression.
Dr. Andreas Leiherer
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 100 words) can be sent to the Editorial Office for announcement on this website.
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. International Journal of Molecular Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. There is an Article Processing Charge (APC) for publication in this open access journal. For details about the APC please see here. 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
- machine learning
- bioinformatics
- deep learning
- multi-omics approaches
- genetic risk factors
- drug interactions
- precision medicine
- neurodegenerative diseases
- disease diagnosis
- epidemic prediction
