About
Rare disorders, also known as orphan diseases, affect a small percentage of the population but collectively impact millions of individuals worldwide. These conditions often present unique challenges due to limited research, lack of awareness, and scarce resources dedicated to their study. Patients frequently face delayed diagnoses and limited treatment options, leading to significant impacts on their quality of life and overall health outcomes.
IgMin Research - A Biomed & Engineering Open Access Journal is committed to advancing the understanding and management of rare disorders by publishing cutting-edge research across biology, medicine, engineering, and general sciences. We aim to foster interdisciplinary collaboration to develop innovative diagnostic tools, effective therapies, and comprehensive care strategies that can transform the lives of those affected by these conditions.

Why Publish with us?
- Global Visibility – Indexed in major databases
- Fast Peer Review – Decision within 14–21 days
- Open Access – Maximize readership and citation
- Multidisciplinary Scope – Biology, Medicine and Engineering
- Editorial Board Excellence – Global experts involved
- University Library Indexing – Via OCLC
- Permanent Archiving – CrossRef DOI
- Affordable APCs with discounts
- High Citation Potential
- Professional Layout & Author Support
Which articles are now trending?
Research Articles
- A Comprehensive Methodology for Assessing the Business Reputation of Industrial and Production Personnel
- Homologous Series of Chemical Compounds in Three-component Systems (Aa+ – Bb+ – Cc–) and (Zn2+ - Ge4+ - P3-) in Generalized Form
- Investigation and Energy Modeling of New Generation Environmentally Friendly Energy Source Thorium Fueled Molten Salt Reactors
- Efficacy of Different Concentrations of Insect Growth Regulators (IGRs) on Maize Stem Borer Infestation
- Enhancing Material Property Predictions through Optimized KNN Imputation and Deep Neural Network Modeling
- From Traditionalism to Algorithms: Embracing Artificial Intelligence for Effective University Teaching and Learning
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