Immunogenomics is a new research field, which addresses the interface between host and (pathogen) proteome, bridging informatics technology, genomics, proteomics, immunology and clinical medicine. The switch from the paradigm of solely hypothesis-driven immunological research to a more interactive and flexible relationship between classical research and a new discovery-driven approach is termed immunogenomics. This review will focus on the immunogenomics and recent discoveries in Immunogenomics, which are leading to insights into novel immunomodulatory therapies. The research regarding the different aspects of immunogenomics; rather than providing a comprehensive review, we will highlight various factors that influence immunogenomics and how modulation of the immune response may be incorporated into future trends.

A lot of research on the prevalence of arthritis in India population has been carried out. However no studies on the genetic relationships within groups of arthritic patients in India have been reported. The current study focuses on analyzing the genetic diversity between patients suffering from the various types of arthritis with reference to factors inducing its onset. A total of 36 patients suffering from different types of arthritis were analyzed with reference to the age, gender, BMI, family history, hemoglobin and thyroid profile. The variation in the genetic profile was also analyzed using the RAPD technique. Data analysis showed patients suffering from arthritis to be at a greater risk of thyroid disorders, however the type of arthritis played a significant role. A distinct correlation between the genetic variation and presence of arthritis including its type was observed.

This article reviews different aspects of protein engineering technologies such as protein screening, NMR, EM & x-ray crystallography, In silico protein structure, protein cell free technologies, protein chips and arrays, custom peptide synthesis as well as nanoscale / microscale separation or purification methods briefly and where they are being used to solve protein queries.

Genomic and proteomic approaches together promise to reveal a multidimensional view of a biological system. As compared to Genomic approaches, Proteomic studies have their fair amount of limitations. The technical issues troubling proteomic approaches include gel-to-gel reproducibility, biases toward identifying similar proteins in unrelated proteomic studies, and reliability of protein extraction methods. Many types of information cannot be obtained from the study of genes alone because proteins not genes are responsible for the phenotypes of cells. Mechanisms of disease, aging and the effects of the environment cannot be explained solely by the genome because through the study of proteins can protein modifications be analyzed and the targets of drugs of identified.

Oncogenomics is new research sub-field of genomics, which applies high throughput technologies to characterize genes associated with cancer and synonymous with cancer genomics. The goal of oncogenomics is to identify new oncogenes or tumor suppressor genes that may provide new insights into cancer diagnosis, predicting clinical outcome of cancers, and new targets for cancer therapies. Oncoproteomics is the term used to describe the application of proteomic technologies in oncology and parallels the related field of oncogenomics. It is now contributing to the development of personalized management of cancer. Genomics has generated a wealth of data that is now being used to identify additional molecular alterations associated with cancer development. Mapping these alterations in the cancer genome is a critical first step in dissecting oncological pathways.

Metabolomics is the study of metabolite profiles in biological and pathological samples (urine, plasma, saliva, blood fat biopsies, plant cells, bacteria viruses and fungi. The metabolome is the most predictive phenotype: consequently, the comprehensive and quantitative research study of metabolites is a desirable tool for diagnosing disease, Identifying new therapeutic targets and enabling appropriate treatments. In addition to other Mass Spectrometry (MS) methodologies used for determining the localization of small molecules in tissue, MALDI-TOF/TOF can also be used to detect drugs and their metabolites in tissue without the burden of matrix interference.

Toxicogenomics is emerging field give idea of the application of large-scale differential gene expression data to toxicology, starting to influence drug discovery and development in the pharmaceutical industry. Its future potential in cancer pathogenesis, study of poisons and poisoning and has an ancient and venerable history. Toxicogenomics is the merging of toxicology with technologies that have been developed, together with bioinformatics, to identify and quantify global gene expression changes for gene therapy. Immunotoxic processes and the development of in vitro screening assays is therefore expected to be of value for mechanistic insight into immunotoxicity and hazard identification of existing and novel compounds. Successful application of toxicogenomic approaches, such as DNA microarrays, inextricably relies on appropriate data management, the ability to extract knowledge from massive amounts of data and the availability of functional information for data interpretation. Toxicogenomics is considered a valuable tool for reducing pharmaceutical candidate attrition by facilitating earlier identification, prediction and understanding of toxicities. Pharmaco-epidemiological (toxicogenomics) data is now available for both antiepileptic drugs, evidence for human carcinogenicity. Therapeutic researches converge triad of rejuvenation, regeneration or replacement strategies that rely on self-healing processes, stem cell regeneration organ transplantation. Metastases studies usually display more genetic changes than the primary tumour. Helix-loop-helix application in translational and functional toxicogenomics transcription factors has been implicated in diverse cellular processes such as proliferation, apoptosis, differentiation, and migration.