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The Bioinformatics is the field of science in which biology, computer science, and information technology merge into a single discipline. The ultimate goal of the field is to enable the discovery of new biological insights as well as to create a global perspective from which unifying principles in biology can be discerned. There are three important sub- disciplines within bioinformatics:the development of new algorithms and statistics with which to assess relationships among members of large data sets; the analysis and interpretation of various types of data including nucleotide and amino acid sequences, protein domains, and protein structures; the development and implementation of tools that enable efficient access and management of different types of information.
The definition of bioinformatics is not universally agreed upon. Generally speaking, define it as the creation and development of advanced information and computational technologies for problems in biology, most commonly molecular biology (but increasingly in other areas of biology). As such, it deals with methods for storing, retrieving and analyzing biological data, such as nucleic acid (DNA/ RNA) and protein sequences, structures, functions, pathways and genetic interactions. Some people construe bioinformatics more narrowly, and include only those issues dealing with the management of genome project sequencing data. Others construe bioinformatics more broadly and include all areas of computational biology, including population modeling and numerical simulations.
Roughly, bioinformatics describes any use of computers to handle biological information. In practice the definition used by most people is narrower; bioinformatics to them is a synonym for "computational molecular biology" - the use of computers to characterise the molecular components of living things
In bioinformatics Computers are used to gather, store, analyze and integrate biological and genetic information which can then be applied to gene-based drug discovery and development. The need for Bioinformatics capabilities has been precipitated by the explosion of publicly available genomic information resulting from the Human Genome Project. The goal of this project - determination of the sequence of the entire human genome (approximately three billion base pairs) . The science of Bioinformatics, which is the melding of molecular biology with computer science, is essential to the use of genomic information in understanding human diseases and in the identification of new molecular targets for drug discovery. In recognition of this, many universities, government institutions and pharmaceutical firms have formed bioinformatics groups, consisting of computational biologists and bioinformatics computer scientists. Such groups will be key to unraveling the mass of information generated by large scale sequencing efforts underway in laboratories around the world.
Molecular diagnostics is a rapidly advancing field in which insights into disease mechanisms are being elucidated by use of new gene-based biomarkers. Until recently, diagnostic and prognostic assessment of diseased tissues and tumors relied heavily on indirect indicators that permitted only general classifications into broad histologic or morphologic subtypes and did not take into account the alterations in individual gene expression. Global expression analysis using microarrays now allows for simultaneous interrogation of the expression of thousands of genes in a high-throughput fashion and offers unprecedented opportunities to obtain molecular signatures of the state of activity of diseased cells and patient samples. Microarray analysis may provide invaluable information on disease pathology, progression, resistance to treatment, and response to cellular microenvironments and ultimately may lead to improved early diagnosis and innovative therapeutic approaches for cancer.
Microarray methods were initially developed to study differential gene expression using complex populations of RNA . Refinements of these methods now permit the analysis of copy number imbalances and gene amplification of DNA and have recently been applied to the systematic analysis of expression at the protein level . Many of the guiding principles of global analysis using microarrays are, in principle, applicable at the RNA, DNA, or protein level.
Expression Profiling Applied to Cancer Biology
Cancer is caused by the accumulation of genetic and epigenetic changes resulting from the altered sequence or expression of cancer-related genes, such as oncogenes or tumor suppressor genes, as well as genes involved in cell cycle control, apoptosis, adhesion, DNA repair, and angiogenesis. Because gene expression profiles provide a snapshot of cell functions and processes at the time of sample preparation, comprehensive combinatorial analysis of the gene expression patterns of thousands of genes in tumor cells and comparison to the expression profile obtained with healthy cells should provide insights concerning consistent changes in gene expression that are associated with tumor cellular dysfunction and any concomitant regulatory pathways. Microarray technology has been widely used in the past 3 years to investigate tumor classification, cancer progression, and chemotherapy resistance and sensitivity.
Cancer grows out of normal cells in the body. Normal cells multiply when the body needs them, and die when the body doesn't need them. Cancer appears to occur when the growth of cells in the body is out of control and cells divide too quickly. It can also occur when cells forget how to die.
There are many different kinds of cancer. Cancer can develop in almost any organ or tissue, such as the lung, colon, breast, skin, bones, or nerve tissue. Breast cancer is a cancer that starts in the tissues of the breast. There are two main types of breast cancer: Ductal carcinoma starts in the tubes (ducts), that move milk from the breast to the nipple. Most breast cancers are of this type. Lobular carcinoma starts in the parts of the breast, called lobules, that produce milk. In rare cases, breast cancer can start in other areas of the breast. Breast cancer may be invasive or noninvasive. Invasive means it has spread from the milk duct or lobule to other tissues in the breast. Noninvasive means it has not yet invaded other breast tissue. Noninvasive breast cancer is called "in situ."
The breast cancer stage is based on the results of testing that is done on the tumor and lymph nodes removed during surgery and other tests.Stage 0 (carcinoma in situ) ,in this stage There are 3 types of breast carcinoma in situ .Ductal carcinoma in situ (DCIS) is a noninvasive condition in which abnormal cells are found in the lining of a breast duct. The abnormal cells have not spread outside the duct to other tissues in the breast. In some cases, DCIS may become invasive cancer and spread to other tissues. At this time, there is no way to know which lesions could become invasive. Lobular carcinoma in situ (LCIS) is a condition in which abnormal cells are found in the lobules of the breast. This condition seldom becomes invasive cancer. However, having LCIS in one breast increases the risk of developing breast cancer in either breast. Paget disease of the nipple is a condition in which abnormal cells are found in the nipple only.
In stage I, cancer has formed. Stage I is divided into stages IA and IB. In stage IA, the tumor is 2 centimeters or smaller. Cancer has not spread outside the breast.In stage IB, small clusters of breast cancer cells (larger than 0.2 millimeter but not larger than 2 millimeters) are found in the lymph nodes and either no tumor is found in the breast or the tumor is 2 centimeters or smaller.
Stage II is divided into stages IIA and IIB. In stage IIA no tumor is found in the breast or the tumor is 2 centimeters or smaller. Cancer (larger than 2 millimeters) is found in 1 to 3 axillary lymph nodes or in the lymph nodes near the breastbone or the tumor is larger than 2 centimeters but not larger than 5 centimeters. Cancer has not spread to the lymph nodes. In stage IIB, the tumor is larger than 2 centimeters but not larger than 5 centimeters. Small clusters of breast cancer cells (larger than 0.2 millimeter but not larger than 2 millimeters) are found in the lymph nodes or larger than 2 centimeters but not larger than 5 centimeters. Cancer has spread to 1 to 3 axillary lymph nodes or to the lymph nodes near the breastbone or larger than 5 centimeters. Cancer has not spread to the lymph nodes.
Stage III is divided into stages IIIA ,IIIB and IIIC.In stage IIIA no tumor is found in the breast or the tumor may be any size. Cancer is found in 4 to 9 axillary lymph nodes or in the lymph nodes near the breastbone or the tumor is larger than 5 centimeters. Small clusters of breast cancer cells (larger than 0.2 millimeter but not larger than 2 millimeters) are found in the lymph nodes; or the tumor is larger than 5 centimeters. Cancer has spread to 1 to 3 axillary lymph nodes or to the lymph nodes near the breastbone In stage IIIB, the tumor may be any size and cancer has spread to the chest wall and/or to the skin of the breast and caused swelling or an ulcer. Also, cancer may have spread up to 9 axillary lymph nodes or the lymph nodes near the breastbone.
In stage IIIC, no tumor is found in the breast or the tumor may be any size. Cancer may have spread to the skin of the breast and caused swelling or an ulcer and/or has spread to the chest wall. Also, cancer has spread to 10 or more axillary lymph nodes or lymph nodes above or below the collarbone or axillary lymph nodes and lymph nodes near the breastbone. For treatment, stage IIIC breast cancer is divided into operable and inoperable stage IIIC.
In stage IV, cancer has spread to other organs of the body, most often the bones, lungs, liver, or brain.
Dna microarray technology has led to an explosion of oncogenomic analyses, generating a wealth of data and uncovering the complex gene expression patterns of cancer. Unfortunately, due to the lack of a unifying bioinformatic resource, the majority of these data sit stagnant and disjointed following publication, massively underutilized by the cancer research community. the oncomine is a cancer microarray database and web-based data-mining platform aimed at facilitating discovery from genome-wide expression analyses. To date, oncomine contains 65 gene expression datasets comprising nearly 48 million gene expression measurements form over 4700 microarray experiments. Differential expression analyses comparing most major types of cancer with respective normal tissues as well as a variety of cancer subtypes and clinical-based and pathology-based analyses are available for exploration. Data can be queried and visualized for a selected gene across all analyses or for multiple genes in a selected analysis. Furthermore, gene sets can be limited to clinically important annotations including secreted, kinase, membrane, and known gene-drug target pairs to facilitate the discovery of novel biomarkers and therapeutic targets.
Gene expression profiling with DNA microarrays has emerged as a powerful approach to study the cancer transcriptome. More than 100 published studies have presented analyses of human cancer samples, identifying gene expression signatures for most major cancer types and subtypes, and uncovering gene expression patterns that correlate with various characteristics of tumors including tumor grade or differentiation state, metastatic potential, and patient survival . Also, novel tissue and serum biomarkers as well as potential therapeutic targets have been identified using these genome-wide screens. These discoveries highlight the remarkable impact that DNA microarrays have had on cancer research.; however. For most published microarray studies, which may comprise thousands of gene measurements across tens or hundreds of cancer specimens, the authors have presented one interpretation of their data and have reported on only a subset of genes that demonstrate their particular hypothesis. The complete microarray datasets are sometimes made available as supplementary data, but even if that is the case, the datasets often sit as cryptic text files, stored and processed in an unsystematic manner, and thus only useful to those with computational expertise. Although standards have now been set for recording and exchanging microarray data , and authors have been urged to provide their complete datasets upon publication , the full potential of cancer microarray data will only be reached when it is unified, logically analyzed, and made easily accessible to the cancer research community.