![]() In XML files, structured data are bounded by tags and attributes. Information encoded in XML is easy to read and understand, and easy to process by computers. XML is simpler than SGML, but it allows the use of richly structured documents over the Internet. It was derived from SGML (Standard Generalized Markup Language), the international standard for defining descriptions of the structure and content of different types of electronic documents. XML allows to define tags and document structures for own context-specific use. It is designed to improve the functionality of the Web by enabling more flexible and adaptable information identification and presentation. The Extensible Markup Language (XML) is a standard created by the World Wide Web Consortium (W3C) for characterizing the content and structure of documents. Since there are also some technical problems arising from the diversity of computer hardware and software, there is a need for such a data form, that can be handled by any computer and which can be easily presented on any platform. Due to ambiguity of terms, a search for a particular term often retrieves results for unrelated entities. Without standardized nomenclature the information extraction (IE) about a particular subject from various resources is difficult. ![]() Processing of biomedical texts presents many challenges such as in the areas of terminology or ontology building, information extraction from texts, knowledge discovery from collections of documents, as well as sharing and integrating knowledge from factual and textual data bases, semantic annotation, etc. automated natural language processing (NLP) techniques. Biomedical data mining attempts to extract information from biomedical databases by using e.g. Systems biology researchers need to integrate disparate information from multiple public sources to merge with their own experimental data to generate models of processes. Clinicians and researchers could benefit from a more consolidated and unified view of the available biomedical data. ![]() There is an increasing need for tools and services capable of integrating information from a variety of sources. Further, the user has often difficulties in assessing the quality of data. First of all, there may not be that much data for these diseases and secondly it may be very difficult to find and collect. The scattering of the disease-related information to literature and Internet is a big obstacle especially for those interested in rare diseases. Still, all these pieces of information can contain clues to understanding the fundamental defects at molecular level and can help to develop targeted treatments. In addition, it is more and more difficult to publish results in scientific journals only from a few cases even when they are interesting. It is often difficult to find comprehensive and validated biomedical information related to rare diseases. One doctor usually has only a few patients with a disease. Most hereditary diseases are rare and the diagnosed patients for a condition are often randomly spread out in the world. The biomedical informatics holds great promise for developing informatics methods that will be crucial in the development of genomic medicine. This far, the knowledge of genetics has had a large role in the health care of only a few patients and a small role in the health care of many. The new knowledge can be applied to the prevention, diagnosis and treatment of diseases. The number of identified genetic diseases has increased exponentially. The completion of the draft sequence of the human genome and advances in molecular biology provide new opportunities to increase our understanding of the role of genetic factors in human health and disease. ![]() ![]() Deciphering the roles of genes in human health and disease is a grand challenge for many reasons, including impediments to defining phenotypes, difficulties in identifying and quantifying environmental effects, technical problems in generating genotypic information, and the difficulties of studying humans. Biomedical information is often very complex. ![]()
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