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54-477: IMGT or the international ImMunoGeneTics information system is a collection of databases and resources for immunoinformatics , particularly the V, D, J, and C gene sequences, as well as a providing other tools and data related to the adaptive immune system . IMGT/LIGM-DB, the first and still largest database hosted as part of IMGT contains reference nucleotide sequences for 360 species' T-cell receptor and immunoglobulin molecules, as of 2023. These genes encode

108-430: A semantic web , text mining can find content based on meaning and context (rather than just by a specific word). Additionally, text mining software can be used to build large dossiers of information about specific people and events. For example, large datasets based on data extracted from news reports can be built to facilitate social networks analysis or counter-intelligence . In effect, the text mining software may act in

162-440: A better understanding of immune responses and their role during normal, diseased and reconstitution states. Computational immunology is a part of immunomics, which is focused on analyzing large-scale experimental data. Computational immunology began over 90 years ago with the theoretic modeling of malaria epidemiology. At that time, the emphasis was on the use of mathematics to guide the study of disease transmission. Since then,

216-583: A database of monoclonal antibodies . Now maintained by the HLA Informatics Group , the primary reference for human HLA, IPD-IMGT/HLA Database, originated in part with IMGT. It was merged with the Immuno Polymorphism Database in 2003 to form the current reference. Since 2015, IMGT has been headed by Sofia Kossida. Immunoinformatics The immune system is a complex system of the human body and understanding it

270-1067: A great help. These models were very useful in characterizing the behavior and spread of infectious disease, by understanding the dynamics of the pathogen in the host and the mechanisms of host factors which aid pathogen persistence. Examples include Plasmodium falciparum and nematode infection in ruminants. Much has been done in understanding immune responses to various pathogens by integrating genomics and proteomics with bioinformatics strategies. Many exciting developments in large-scale screening of pathogens are currently taking place. National Institute of Allergy and Infectious Diseases (NIAID) has initiated an endeavor for systematic mapping of B and T cell epitopes of category A-C pathogens. These pathogens include Bacillus anthracis (anthrax), Clostridium botulinum toxin (botulism), Variola major (smallpox), Francisella tularensis (tularemia), viral hemorrhagic fevers, Burkholderia pseudomallei , Staphylococcus enterotoxin B, yellow fever, influenza, rabies, Chikungunya virus etc. Rule-based systems have been reported for

324-485: A review is for the product. Such an analysis may need a labeled data set or labeling of the affectivity of words. Resources for affectivity of words and concepts have been made for WordNet and ConceptNet , respectively. Text has been used to detect emotions in the related area of affective computing. Text based approaches to affective computing have been used on multiple corpora such as students evaluations, children stories and news stories. The issue of text mining

378-433: A selective growth advantage. Recently it has been very important to determine the novel mutations. Genomics and proteomics techniques are used worldwide to identify mutations related to each specific cancer and their treatments. Computational tools are used to predict growth and surface antigens on cancerous cells. There are publications explaining a targeted approach for assessing mutations and cancer risk. Algorithm CanPredict

432-483: A traditional part of social sciences and media studies for a long time. The automation of content analysis has allowed a " big data " revolution to take place in that field, with studies in social media and newspaper content that include millions of news items. Gender bias , readability , content similarity, reader preferences, and even mood have been analyzed based on text mining methods over millions of documents. The analysis of readability, gender bias and topic bias

486-450: A way to improve their results. Within the public sector, much effort has been concentrated on creating software for tracking and monitoring terrorist activities . For study purposes, Weka software is one of the most popular options in the scientific world, acting as an excellent entry point for beginners. For Python programmers, there is an excellent toolkit called NLTK for more general purposes. For more advanced programmers, there's also

540-475: A wide variety of government, research, and business needs. All these groups may use text mining for records management and searching documents relevant to their daily activities. Legal professionals may use text mining for e-discovery , for example. Governments and military groups use text mining for national security and intelligence purposes. Scientific researchers incorporate text mining approaches into efforts to organize large sets of text data (i.e., addressing

594-481: Is a knowledge-based search engine for biomedical texts. Text mining techniques also enable us to extract unknown knowledge from unstructured documents in the clinical domain Text mining methods and software is also being researched and developed by major firms, including IBM and Microsoft , to further automate the mining and analysis processes, and by different firms working in the area of search and indexing in general as

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648-420: Is a truism that 80% of business-relevant information originates in unstructured form, primarily text. These techniques and processes discover and present knowledge – facts, business rules , and relationships – that is otherwise locked in textual form, impenetrable to automated processing. Subtasks—components of a larger text-analytics effort—typically include: Text mining technology is now broadly applied to

702-557: Is also involved in the study of text encryption / decryption . A range of text mining applications in the biomedical literature has been described, including computational approaches to assist with studies in protein docking , protein interactions , and protein-disease associations. In addition, with large patient textual datasets in the clinical field, datasets of demographic information in population studies and adverse event reports, text mining can facilitate clinical studies and precision medicine. Text mining algorithms can facilitate

756-440: Is based on similar concepts and tools, such as sequence alignment and protein structure prediction tools. Immunomics is a discipline like genomics and proteomics . It is a science, which specifically combines immunology with computer science , mathematics , chemistry , and biochemistry for large-scale analysis of immune system functions. It aims to study the complex protein–protein interactions and networks and allows

810-422: Is being used in business, particularly, in marketing, such as in customer relationship management . Coussement and Van den Poel (2008) apply it to improve predictive analytics models for customer churn ( customer attrition ). Text mining is also being applied in stock returns prediction. Sentiment analysis may involve analysis of products such as movies, books, or hotel reviews for estimating how favorable

864-440: Is due to responses of an IgE antibody -producing B cell and/or of a T cell to a particular allergen . Therefore, immunogenicity studies focus mainly on identifying recognition sites of B-cells and T-cells for allergens. The three-dimensional structural properties of allergens control their allergenicity. The use of immunoinformatics tools can be useful to predict protein allergenicity and will become increasingly important in

918-560: Is no exception in copyright law of Australia for text or data mining within the Copyright Act 1968 . The Australian Law Reform Commission has noted that it is unlikely that the "research and study" fair dealing exception would extend to cover such a topic either, given it would be beyond the "reasonable portion" requirement. Until recently, websites most often used text-based searches, which only found documents containing specific user-defined words or phrases. Now, through use of

972-606: Is of importance to publishers who hold large databases of information needing indexing for retrieval. This is especially true in scientific disciplines, in which highly specific information is often contained within the written text. Therefore, initiatives have been taken such as Nature's proposal for an Open Text Mining Interface (OTMI) and the National Institutes of Health 's common Journal Publishing Document Type Definition (DTD) that would provide semantic cues to machines to answer specific queries contained within

1026-479: Is one of the most challenging topics in biology. Immunology research is important for understanding the mechanisms underlying the defense of human body and to develop drugs for immunological diseases and maintain health. Recent findings in genomic and proteomic technologies have transformed the immunology research drastically. Sequencing of the human and other model organism genomes has produced increasingly large volumes of data relevant to immunology research and at

1080-570: Is roughly synonymous with text mining; indeed, Ronen Feldman modified a 2000 description of "text mining" in 2004 to describe "text analytics". The latter term is now used more frequently in business settings while "text mining" is used in some of the earliest application areas, dating to the 1980s, notably life-sciences research and government intelligence. The term text analytics also describes that application of text analytics to respond to business problems, whether independently or in conjunction with query and analysis of fielded, numerical data. It

1134-631: Is the process of deriving high-quality information from text . It involves "the discovery by computer of new, previously unknown information, by automatically extracting information from different written resources." Written resources may include websites , books , emails , reviews , and articles. High-quality information is typically obtained by devising patterns and trends by means such as statistical pattern learning . According to Hotho et al. (2005), there are three perspectives of text mining: information extraction , data mining , and knowledge discovery in databases (KDD). Text mining usually involves

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1188-531: Is very much important to design and justify the models to predict various molecular targets. Computational immunology tools is the game between experimental data and mathematically designed computational tools. Allergies , while a critical subject of immunology, also vary considerably among individuals and sometimes even among genetically similar individuals. The assessment of protein allergenic potential focuses on three main aspects: (i) immunogenicity; (ii) cross-reactivity; and (iii) clinical symptoms. Immunogenicity

1242-509: Is viewed as being legal. As text mining is transformative, meaning that it does not supplant the original work, it is viewed as being lawful under fair use. For example, as part of the Google Book settlement the presiding judge on the case ruled that Google's digitization project of in-copyright books was lawful, in part because of the transformative uses that the digitization project displayed—one such use being text and data mining. There

1296-486: The Codex alimentarius , a protein is potentially allergenic if it possesses an identity of ≥6 contiguous amino acids or ≥35% sequence similarity over an 80 amino acid window with a known allergen. Though there are rules, their inherent limitations have started to become apparent and exceptions to the rules have been well reported In the study of infectious diseases and host responses, the mathematical and computer models are

1350-617: The Gensim library, which focuses on word embedding-based text representations. Text mining is being used by large media companies, such as the Tribune Company , to clarify information and to provide readers with greater search experiences, which in turn increases site "stickiness" and revenue. Additionally, on the back end, editors are benefiting by being able to share, associate and package news across properties, significantly increasing opportunities to monetize content. Text analytics

1404-1003: The Nucleic Acids Research (NAR) Database Collection , which are given in the following table, together with some more immune related databases. The information given in the table is taken from the database descriptions in NAR Database Collection . Online resources for allergy information are also available on http://www.allergen.org . Such data is valuable for investigation of cross-reactivity between known allergens and analysis of potential allergenicity in proteins. The Structural Database of Allergen Proteins (SDAP) stores information of allergenic proteins. The Food Allergy Research and Resource Program (FARRP) Protein Allergen -Online Database contains sequences of known and putative allergens derived from scientific literature and public databases. Allergome emphasizes

1458-497: The ability of a particular peptide to gain access to the MHC class I pathway. Artificial neural network (ANN), a computer model was used to study peptide binding to human TAP and its relationship with MHC class I binding. The affinity of HLA-binding peptides for TAP was found to differ according to the HLA supertype concerned using this method. This research could have important implications for

1512-498: The annotation of allergens that result in an IgE-mediated disease. A variety of computational, mathematical and statistical methods are available and reported. These tools are helpful for collection, analysis, and interpretation of immunological data. They include text mining , information management, sequence analysis, analysis of molecular interactions, and mathematical models that enable advanced simulations of immune system and immunological processes. Attempts are being made for

1566-530: The annotation of the building block regions and their role is unique within the genome. To standardize terminology and references, the IMGT-NC was created in 1992 and recognized by the International Union of Immunological Societies as a nomenclature subcommittee. Other tools include IMGT/Collier-de-Perles, a method for two dimensional representation of receptor amino acid sequences, and IMGT/mAb-DB,

1620-404: The application of natural language processing (NLP), different types of algorithms and analytical methods. An important phase of this process is the interpretation of the gathered information. A typical application is to scan a set of documents written in a natural language and either model the document set for predictive classification purposes or populate a database or search index with

1674-568: The automated extraction and curation of influenza A records. This development would lead to the development of an algorithm which would help to identify the conserved regions of pathogen sequences and in turn would be useful for vaccine development. This would be helpful in limiting the spread of infectious disease. Examples include a method for identification of vaccine targets from protein regions of conserved HLA binding and computational assessment of cross-reactivity of broadly neutralizing antibodies against viral pathogens. These examples illustrate

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1728-440: The design of peptide based immuno-therapeutic drugs and vaccines. It shows the power of the modeling approach to understand complex immune interactions. There exist also methods which integrate peptide prediction tools with computer simulations that can provide detailed information on the immune response dynamics specific to the given pathogen's peptides . Cancer is the result of somatic mutations which provide cancer cells with

1782-708: The extraction of interesting and complex patterns from non-structured text documents in the immunological domain, such as categorization of allergen cross-reactivity information, identification of cancer-associated gene variants and the classification of immune epitopes. Immunoinformatics is using the basic bioinformatics tools such as ClustalW, BLAST, and TreeView, as well as specialized immunoinformatics tools, such as EpiMatrix, IMGT/V-QUEST for IG and TR sequence analysis, IMGT/ Collier-de-Perles and IMGT/StructuralQuery for IG variable domain structure analysis. Methods that rely on sequence comparison are diverse and have been applied to analyze HLA sequence conservation, help verify

1836-434: The field has expanded to cover all other aspects of immune system processes and diseases. After the recent advances in sequencing and proteomics technology, there have been many fold increase in generation of molecular and immunological data. The data are so diverse that they can be categorized in different databases according to their use in the research. Until now there are total 31 different immunological databases noted in

1890-465: The host immune system dynamics in response to artificial immunity induced by vaccination strategies. Other simulation tools use predicted cancer peptides to forecast immune specific anticancer responses that is dependent on the specified HLA. These resources are likely to grow significantly in the near future and immunoinformatics will be a major growth area in this domain. Text mining Text mining , text data mining ( TDM ) or text analytics

1944-468: The information extracted. The document is the basic element when starting with text mining. Here, we define a document as a unit of textual data, which normally exists in many types of collections. Text analytics describes a set of linguistic , statistical , and machine learning techniques that model and structure the information content of textual sources for business intelligence , exploratory data analysis , research , or investigation. The term

1998-406: The key actors, the key communities or parties, and general properties such as robustness or structural stability of the overall network, or centrality of certain nodes. This automates the approach introduced by quantitative narrative analysis, whereby subject-verb-object triplets are identified with pairs of actors linked by an action, or pairs formed by actor-object. Content analysis has been

2052-523: The mining of in-copyright works (such as by web mining ) without the permission of the copyright owner is illegal. In the UK in 2014, on the recommendation of the Hargreaves review , the government amended copyright law to allow text mining as a limitation and exception . It was the second country in the world to do so, following Japan , which introduced a mining-specific exception in 2009. However, owing to

2106-463: The nature of specificity in immune network and immunogenicity. For example, it was useful to examine the functional relationship between TAP peptide transport and HLA class I antigen presentation. TAP is a transmembrane protein responsible for the transport of antigenic peptides into the endoplasmic reticulum, where MHC class I molecules can bind them and presented to T cells. As TAP does not bind all peptides equally, TAP-binding affinity could influence

2160-444: The origins of human immunodeficiency virus (HIV) sequences, and construct homology models for the analysis of hepatitis B virus polymerase resistance to lamivudine and emtricitabine. There are also some computational models which focus on protein–protein interactions and networks. There are also tools which are used for T and B cell epitope mapping, proteasomal cleavage site prediction, and TAP– peptide prediction. The experimental data

2214-530: The possibility for scholars to analyze millions of documents in multiple languages with very limited manual intervention. Key enabling technologies have been parsing, machine translation , topic categorization , and machine learning. The automatic parsing of textual corpora has enabled the extraction of actors and their relational networks on a vast scale, turning textual data into network data. The resulting networks, which can contain thousands of nodes, are then analyzed by using tools from network theory to identify

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2268-760: The power of immunoinformatics applications to help solve complex problems in public health. Immunoinformatics could accelerate the discovery process dramatically and potentially shorten the time required for vaccine development. Immunoinformatics tools have been used to design the vaccine against SARS-CoV-2, Dengue virus and Leishmania. Using this technology it is possible to know the model behind immune system. It has been used to model T-cell-mediated suppression, peripheral lymphocyte migration, T-cell memory, tolerance, thymic function, and antibody networks. Models are helpful to predicts dynamics of pathogen toxicity and T-cell memory in response to different stimuli. There are also several models which are helpful in understanding

2322-585: The problem of unstructured data ), to determine ideas communicated through text (e.g., sentiment analysis in social media ) and to support scientific discovery in fields such as the life sciences and bioinformatics . In business, applications are used to support competitive intelligence and automated ad placement , among numerous other activities. Many text mining software packages are marketed for security applications , especially monitoring and analysis of online plain text sources such as Internet news , blogs , etc. for national security purposes. It

2376-1047: The process of structuring the input text (usually parsing , along with the addition of some derived linguistic features and the removal of others, and subsequent insertion into a database ), deriving patterns within the structured data , and finally evaluation and interpretation of the output. 'High quality' in text mining usually refers to some combination of relevance , novelty , and interest. Typical text mining tasks include text categorization , text clustering , concept/entity extraction, production of granular taxonomies, sentiment analysis , document summarization , and entity relation modeling ( i.e. , learning relations between named entities ). Text analysis involves information retrieval , lexical analysis to study word frequency distributions, pattern recognition , tagging / annotation , information extraction , data mining techniques including link and association analysis, visualization , and predictive analytics . The overarching goal is, essentially, to turn text into data for analysis, via

2430-456: The proteins which are the foundation of adaptive immunity, which allows highly specific recognition and memory of pathogens. IMGT was founded in June, 1989, by Marie-Paule Lefranc , an immunologist working at University of Montpellier . The project was presented to the 10th Human Genome Mapping Workshop, and resulted in the recognition of V, D, J, and C regions as genes. The first resource created

2484-485: The restriction of the Information Society Directive (2001), the UK exception only allows content mining for non-commercial purposes. UK copyright law does not allow this provision to be overridden by contractual terms and conditions. The European Commission facilitated stakeholder discussion on text and data mining in 2013, under the title of Licenses for Europe. The fact that the focus on

2538-424: The same time huge amounts of functional and clinical data are being reported in the scientific literature and stored in clinical records. Recent advances in bioinformatics or computational biology were helpful to understand and organize these large-scale data and gave rise to new area that is called Computational immunology or immunoinformatics . Computational immunology is a branch of bioinformatics and it

2592-592: The screening of novel foods before their wide-scale release for human use. Thus, there are major efforts under way to make reliable broad based allergy databases and combine these with well validated prediction tools in order to enable the identification of potential allergens in genetically modified drugs and foods. Though the developments are on primary stage, the World Health organization and Food and Agriculture Organization have proposed guidelines for evaluating allergenicity of genetically modified foods. According to

2646-540: The solution to this legal issue was licenses, and not limitations and exceptions to copyright law, led representatives of universities, researchers, libraries, civil society groups and open access publishers to leave the stakeholder dialogue in May 2013. US copyright law , and in particular its fair use provisions, means that text mining in America, as well as other fair use countries such as Israel, Taiwan and South Korea,

2700-423: The stratification and indexing of specific clinical events in large patient textual datasets of symptoms, side effects, and comorbidities from electronic health records, event reports, and reports from specific diagnostic tests. One online text mining application in the biomedical literature is PubGene , a publicly accessible search engine that combines biomedical text mining with network visualization. GoPubMed

2754-440: The text without removing publisher barriers to public access. Academic institutions have also become involved in the text mining initiative: Computational methods have been developed to assist with information retrieval from scientific literature. Published approaches include methods for searching, determining novelty, and clarifying homonyms among technical reports. The automatic analysis of vast textual corpora has created

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2808-500: Was IMGT/LIGM-DB, a reference for nucleotide sequences of T-cell receptor and immunoglobulin of humans, and later vertebrate species. IMGT was created under the auspices of Laboratoire d'ImmunoGénétique Moléculaire at the University of Montpellier as well as French National Centre for Scientific Research (CNRS). As both T-cell receptors and immunoglobulin molecules are built through a process of recombination of nucleotide sequences,

2862-455: Was demonstrated in Flaounas et al. showing how different topics have different gender biases and levels of readability; the possibility to detect mood patterns in a vast population by analyzing Twitter content was demonstrated as well. Text mining computer programs are available from many commercial and open source companies and sources. Under European copyright and database laws ,

2916-529: Was used to indicate how closely a specific gene resembles known cancer-causing genes. Cancer immunology has been given so much importance that the data related to it is growing rapidly. Protein–protein interaction networks provide valuable information on tumorigenesis in humans. Cancer proteins exhibit a network topology that is different from normal proteins in the human interactome. Immunoinformatics have been useful in increasing success of tumour vaccination. Recently, pioneering works have been conducted to analyse

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