Transplantation & Computational Immunology

Transplant immunology is characterized as the resistant reaction that happens when an organ or tissue is moved (joined) starting with one individual then onto the next. Transplantation is the demonstration of exchanging cells, tissues, or organs starting with one site then onto the next. The glitch of an organ framework can be adjusted with the transplantation of an organ (eg, heart, lung, kidney, liver or pancreas) from a contributor.

Computational immunology incorporates the improvement and use of bioinformatics strategies, scientific models and factual procedures for the investigation of resistant framework science. It means to consider the mind boggling protein-protein collaborations and arranges and permits a superior comprehension of invulnerable reactions and their job amid typical, unhealthy and reconstitution states. Computational immunology covers a wide scope of utilizations.

  • Bone Marrow Transplantation
  • Immunotherapeutic drug design
  • The Celeda-seiden model
  • Predicting Epitopes
  • Immunogenic Regions of protein’s
  • Stem Cell Transplantation
  • Transplantation Tolerance
  • Solid Organs Transplantation
  • Chronic Rejection
  • Tolerance induction; xenotransplantation; islet cell transplantation
  • Anti-donor Antibodies & Current Research
  • Potential xenotransplantation
  • Fundamentals of Computational Immunology
  • Computational Modeling
  • Use of Computational Modeling in Immunological Research
  • Use of Computational Modeling in Immunological Research
  • Immunoinformatics & Cyberinfrastructure for Modeling and Analytics
  • Database & Tools in Immunology
  • From Big Data Analytics and Network Inference to Systems Modeling
  • Multistage Modeling: Concepts, Technologies, and Use Cases in Immunology
  • Other Related Topics

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