James Yip Editor at IgMin Research
We seek to unite different scientific sectors to stimulate growth and advance collective expertise.
Biography
Dr. James Yip is an internationally recognized pathologist with extensive expertise in neurological and hematological disorders. He obtained his Master’s degree focusing on transplant immunology at the University of Western Ontario, Canada. He completed his MD degree at Wayne State University, where he contributed extensively to neuroprotection and vascular stroke research at the Department of Neurosurgery. He further completed a fellowship at Weill Cornell Medicine with subspecialization in hematologic
disorders.
Research Interest
T cells, NK cells, CNS neoplasms, hematolymphoid neoplasms
Editor
Work Details
Doctor
Weill Cornell Medicine
Department of Pathology and Laboratory Medicine
USA
Contribution by Topic Area
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
APC – Affordable APCs with discounts
Citation – High Citation Potential
Which articles are now trending?
Research Articles
- Communication Training at Medical School: A Quantitative Analysis
- Gaussian-Transform for the Dirac Wave Function and its Application to the Multicenter Molecular Integral Over Dirac Wave Functions for Solving the Molecular Matrix Dirac Equation
- Optimising the Deployment of a Last-Mile Micromobility Fleet by Accounting for Terrain-Induced Energy Consumption
- Methodology of the Professional-Business Game for the Development of a Cadet Leader in Professional Training Courses (L-1B) of the Tactical Level of Military Education
- Deep Learning-Based Prediction of Nepal Stock Exchange Movements from Financial News Headlines
- Clustering of Three-dimensional (3-D) Objects by Means of Phase- only Digital Holographic Information using Machine Learning
