High throughput sequencing and molecular imaging technologies marked the beginning of a new era for modern translational medicine and personalized healthcare. The impact of having the human sequence and personalized digital images in hand has also created tremendous demands of developing powerful supercomputing, statistical learning and artificial intelligence approaches to handle the massive bioinformatics and personalized healthcare data which will obviously have a profound effect on how biomedical research will be conducted toward the improvement of human health and prolonging human life in the future.

In spite of fast growing burgeoning research activity on bioinformatics and computational molecular physics of living matter, the basic problems in the field still remain unsolved. For example, it is largely unknown how naturally evolved proteins fold their 3-D structure with such functions involving protein-ligand interfaces, molecular signaling, binding efficiencies or protein - DNA interactions. Often it is hard to rationally design drugs effectively as a result of virtually intractable inherent complexity of bio-molecules. The limitations of theoretical biology are real and serious but we can examine or interrogate gene function and protein structure in relation to the environment and available data, thus we can infer the interactive context, structural and functional information as a true collective personalized biomedicine that acts synergistically with all information that are centered on a particular type of disease on an individual human or patient.

The International Society of Intelligent Biological Medicine in partnership with the International Journal of Functional Informatics and Personalized Medicine (www.inderscience.com/ijfipm) and the International Journal of Computational Biology and Drug Design (www.inderscience.com/ijcbdd) touches tomorrow's bioinformatics and personalized medicine throughout today's efforts in promoting the research, education and awareness of the upcoming inter/multidisciplinary field. The development of methodologies in Functional Informatics and Personalized medicine utilizes supercomputing, statistics learning, and artificial intelligence in handling the information and data from biomedical data sets, gene and protein sequence information, patient's genotype, disease phonotype, level of gene expression, lipidomics, and all available biological and clinical information to discover the biological mechanism of living organisms, stratify disease, design new medication, planning a therapy, or initiate a preventative measure that is particularly suited to that human or patient at the time of administration. Advances of functional informatics and personalized medicine make aim on the designing and selection of exact treatment planning or exact right drug, at exact right dose, to the exact right patient, at the exact right time with exact minimum or no side effects. The benefits of functional informatics and personalized medicine approaches utilizing supercomputing and statistical learning are in its "worry free" effectiveness, accuracy, efficacy, safety and speed with exactly right prediction of prognosis. With progress in the high throughput genome sequencing and digital images, biocomputing and medical research have unfolded a series of new, predictive sciences that share the appendage -omics such as genomics, proteomics, lipidomics, metabolomics, cytomics and pharmaconomics. These have promoted new emerging computational, statistical and biomedical approaches to drug design and drug development as well as unleashing the potential of significantly more accurate and more effective personalized diagnosis, therapeutics, and patient care. The emerging high performance computing, statistical learning and artificial intelligence approaches will help discovering the disease variations and developing new approach to disease prevention, treatment and personalized healthcare.
The International Society of Intelligent Biological Medicine (ISIBM) aims to use intelligent methods to study biological medicine. The original idea to form this society came from the organizers of IEEE 7th International Conference on Bioinformatics & Bioengineering with 500 poeple gathered at Harvard Medical, Boston, Massachusetts (IEEE BIBE 2007).
In the fields of bioinformatics, computational biology, and bioengineering, scientists regularly approach important biological and medical problems by using a common set of intelligent methods, such as computational data mining, evolutionary computation, pattern recognition, knowledge representation, databases, combinatorics, stochastic modeling, linguistic methods, robotics, string and graph algorithms, constraint satisfaction, and parallel computation. With such a plethora of intelligent methods, it is essential to provide a platform to bring these scientists together to discuss scientific issues in this fast growing field. ISIBM aims to fill this need. The mission of ISIBM is to facilitate the multidisciplinary development of intelligent methods and to empower creative scientists in these fields to solve biological and medical problems.
ISIBM is registered in the United States as a non-profit academic / professional organization. To know more about the society, please contact Secretary-General Prof. Michelle M. Zhu (mzhu@cs.siu.edu 618-453-6057)