Manoj Bhasin mostly deals with Support vector machine, Epitope, Bioinformatics, Regulation of gene expression and Computational biology. His Support vector machine study combines topics in areas such as Amino acid, Dipeptide, Biological system and Subcellular localization. His Bioinformatics research is multidisciplinary, incorporating perspectives in Inflammation, Cancer stem cell, Carcinogenesis, Progenitor cell and Signal transduction.
His work deals with themes such as Kidney and Mitochondrial biogenesis, which intersect with Inflammation. His Signal transduction study incorporates themes from Transcriptome, Downregulation and upregulation, Upstream and downstream, Insulin and Mitochondrion. His Regulation of gene expression research is multidisciplinary, incorporating elements of Gene expression profiling, T-cell leukemia and CpG site.
Cancer research, Immunology, Internal medicine, Transcriptome and Cell biology are his primary areas of study. His research in Cancer research intersects with topics in Carcinogenesis, Cancer, Prostate cancer, Downregulation and upregulation and Leukemia. His research in Downregulation and upregulation tackles topics such as Inflammation which are related to areas like Insulin.
His research on Immunology often connects related topics like Gene expression profiling. His Internal medicine research integrates issues from Endocrinology, Gene, Oncology and Pathology. His Transcriptome study integrates concerns from other disciplines, such as Meta-analysis, Microarray, Signal transduction, Regulation of gene expression and Cell type.
His primary areas of study are Cancer research, Transcriptome, Cell, Cell biology and Proteomics. His Cancer research research incorporates themes from Cancer, Blockade, Immune system, Immune microenvironment and Leukemia. His Transcriptome research includes themes of Tyrosine kinase, Gene signature, Renal cell carcinoma and Fibroblast growth factor.
His Diabetic foot study also includes fields such as
Manoj Bhasin spends much of his time researching Cancer research, Inflammation, Cell, Cell biology and Myeloid. His Cancer research study combines topics in areas such as Cancer, Blockade, Autacoid, Proinflammatory cytokine and Thromboxane A2. His research in Cancer focuses on subjects like Renal cell carcinoma, which are connected to Downregulation and upregulation.
His work blends Inflammation and Ketorolac studies together. His work carried out in the field of Cell brings together such families of science as Endothelial stem cell, Cytotoxic T cell, Angiogenesis, Immunology and Fibroblast. His research in Cell biology is mostly concerned with Mitochondrion.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
ESLpred: SVM-based method for subcellular localization of eukaryotic proteins using dipeptide composition and PSI-BLAST
Manoj Bhasin;G. P. S. Raghava.
Nucleic Acids Research (2004)
Genomic Counter-Stress Changes Induced by the Relaxation Response
Jeffery A. Dusek;Hasan H Otu;Ann L. Wohlhueter;Manoj Bhasin.
PLOS ONE (2008)
Prediction of CTL epitopes using QM, SVM and ANN techniques.
Manoj Bhasin;G.P.S. Raghava.
PGC-1α promotes recovery after acute kidney injury during systemic inflammation in mice
Mei Tran;Denise Tam;Amit Bardia;Manoj Bhasin.
Journal of Clinical Investigation (2011)
Notch1 contributes to mouse T-cell leukemia by directly inducing the expression of c-myc
Vishva Mitra Sharma;Jennifer Ann Calvo;Kyle M. Draheim;Leslie A. Cunningham.
Molecular and Cellular Biology (2006)
Relaxation Response Induces Temporal Transcriptome Changes in Energy Metabolism, Insulin Secretion and Inflammatory Pathways
Manoj Bhasin;Manoj Bhasin;Jeffery A. Dusek;Bei-Hung Chang;Bei-Hung Chang;Marie G. Joseph.
PLOS ONE (2013)
Support Vector Machine-based Method for Subcellular Localization of Human Proteins Using Amino Acid Compositions, Their Order, and Similarity Search
Aarti Garg;Manoj Bhasin;Gajendra P.S. Raghava.
Journal of Biological Chemistry (2005)
MHCBN: a comprehensive database of MHC binding and non-binding peptides.
Manoj Bhasin;Harpreet Singh;G. P. S. Raghava.
PSLpred: prediction of subcellular localization of bacterial proteins
Manoj Bhasin;Aarti Garg;G. P. S. Raghava.
PGC1α drives NAD biosynthesis linking oxidative metabolism to renal protection
Mei T. Tran;Zsuzsanna K. Zsengeller;Anders H. Berg;Eliyahu V. Khankin.
If you think any of the details on this page are incorrect, let us know.
We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below: