نتایج جستجو برای: prosite

تعداد نتایج: 274  

Journal: :Proceedings. International Conference on Intelligent Systems for Molecular Biology 1998
Kevin Atteson

We present algorithms for the exact computation of the probability that a random string of a certain length matches a given regular expression. These algorithms can be used to determine statistical significance in a variety of pattern searches such as motif searches and gene-finding. This work improves upon work of Kleffe and Langebacker (Kleffe & Langbecker 1990) and of Sewell and Durbin (Sewe...

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Journal: :Frontiers in bioscience : a journal and virtual library 2005
Meena K Sakharkar Vincent T K Chow Kingshuk Ghosh Iti Chaturvedi Pern Chern Lee Sundara Perumal Bagavathi Paul Shapshak Subramanian Subbiah Pandjassarame Kangueane

Human genes are often interrupted by non-coding, intragenic sequences called introns. Hence, the gene sequence is divided into exons (coding segments) and introns (non-coding segments). Consequently, a majority of them are multi exon genes (MEG). However, a considerable amount of single exon genes (SEG) are present in the human genome (approximately 12%). This amount is sizeable and it is impor...

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Journal: :Algorithms 2013
Matteo Comin Davide Verzotto

In biology, the notion of degenerate pattern plays a central role for describing various phenomena. For example, protein active site patterns, like those contained in the PROSITE database, e.g., [FY ]DPC[LIM ][ASG]C[ASG], are, in general, represented by degenerate patterns with character classes. Researchers have developed several approaches over the years to discover degenerate patterns. Altho...

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2007
Peera Liewlom Thanawin Rakthanmanon Kitsana Waiyamai

The purpose of this research is to search for motifs directly at binding and catalytic sites called reactive motifs, and then to predict enzyme functions from the discovered reactive motifs. The main challenge is that the data of binding, or catalytic sites is only available in the range 3.34% of all enzymes, and many of each data provides only one sequence record. The other challenge is the co...

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Journal: :Nucleic acids research 2000
Jorja G. Henikoff Elizabeth A. Greene Shmuel Pietrokovski Steven Henikoff

The Blocks Database WWW (http://blocks.fhcrc.org ) and Email (blocks@blocks.fhcrc.org ) servers provide tools to search DNA and protein queries against the Blocks+ Database of multiple alignments, which represent conserved protein regions. Blocks+ nearly doubles the number of protein families included in the database by adding families from the Pfam-A, ProDom and Domo databases to those from PR...

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1997
H. Ripoche

This paper concerns the use of an object-oriented database for the analysis of protein sequences. We describe proteins either by bibliographic information or by prediction function such as Prosite patterns [2, 5]. We propose to use concept lattices|a tool used in information retrieval to build thesauruses|to classify protein sequences. This classi cation of proteins may help nding sequence alig...

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2005
Yen Kaow Ng Hirotaka Ono Takeshi Shinohara

We consider the problem of finding a set of patterns that best characterizes a set of strings. To this end, Arimura et. al. [3] considered the use of minimal multiple generalizations (mmg) for such characterizations. Given any sample set, the mmgs are, roughly speaking, the most (syntactically) specific set of languages containing the sample within a given class of languages. Takae et. al. [17]...

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Journal: :Bioinformatics 2003
Razif R. Gabdoulline René Hoffmann Florian Leitner Rebecca C. Wade

ProSAT (for Protein Structure Annotation Tool) is a tool to facilitate interactive visualization of non-structure-based functional annotations in protein 3D structures. It performs automated mapping of the functional annotations onto the protein structure and allows functional sites to be readily identified upon visualization. The current version of ProSAT can be applied to large datasets of pr...

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Journal: :Protein engineering, design & selection : PEDS 2004
Andrea Passerini Paolo Frasconi

We present a machine learning method to discriminate between cysteines involved in ligand binding and cysteines forming disulfide bridges. Our method uses a window of multiple alignment profiles to represent each instance and support vector machines with a polynomial kernel as the learning algorithm. We also report results obtained with two new kernel functions based on similarity matrices. Exp...

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2014
Heinz Stockinger Adrian M. Altenhoff Konstantin Arnold Amos Bairoch Frederic Bastian Sven Bergmann Lydie Bougueleret Philipp Bucher Mauro Delorenzi Lydie Lane Philippe Le Mercier Frédérique Lisacek Olivier Michielin Patricia M. Palagi Jacques Rougemont Torsten Schwede Christian von Mering Erik van Nimwegen Daniel Walther Ioannis Xenarios Mihaela Zavolan Evgeny M. Zdobnov Vincent Zoete Ron D. Appel

The SIB Swiss Institute of Bioinformatics (www.isb-sib.ch) was created in 1998 as an institution to foster excellence in bioinformatics. It is renowned worldwide for its databases and software tools, such as UniProtKB/Swiss-Prot, PROSITE, SWISS-MODEL, STRING, etc, that are all accessible on ExPASy.org, SIB's Bioinformatics Resource Portal. This article provides an overview of the scientific and...

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function paginate(evt) { url=/search_year_filter/ var term=document.getElementById("search_meta_data").dataset.term pg=parseInt(evt.target.text) var data={ "year":filter_year, "term":term, "pgn":pg } filtered_res=post_and_fetch(data,url) window.scrollTo(0,0); } function update_search_meta(search_meta) { meta_place=document.getElementById("search_meta_data") term=search_meta.term active_pgn=search_meta.pgn num_res=search_meta.num_res num_pages=search_meta.num_pages year=search_meta.year meta_place.dataset.term=term meta_place.dataset.page=active_pgn meta_place.dataset.num_res=num_res meta_place.dataset.num_pages=num_pages meta_place.dataset.year=year document.getElementById("num_result_place").innerHTML=num_res if (year !== "unfilter"){ document.getElementById("year_filter_label").style="display:inline;" document.getElementById("year_filter_place").innerHTML=year }else { document.getElementById("year_filter_label").style="display:none;" document.getElementById("year_filter_place").innerHTML="" } } function update_pagination() { search_meta_place=document.getElementById('search_meta_data') num_pages=search_meta_place.dataset.num_pages; active_pgn=parseInt(search_meta_place.dataset.page); document.getElementById("pgn-ul").innerHTML=""; pgn_html=""; for (i = 1; i <= num_pages; i++){ if (i===active_pgn){ actv="active" }else {actv=""} pgn_li="
  • " +i+ "
    • "; pgn_html+=pgn_li; } document.getElementById("pgn-ul").innerHTML=pgn_html var pgn_links = document.querySelectorAll('.mypgn'); pgn_links.forEach(function(pgn_link) { pgn_link.addEventListener('click', paginate) }) } function post_and_fetch(data,url) { showLoading() xhr = new XMLHttpRequest(); xhr.open('POST', url, true); xhr.setRequestHeader('Content-Type', 'application/json; charset=UTF-8'); xhr.onreadystatechange = function() { if (xhr.readyState === 4 && xhr.status === 200) { var resp = xhr.responseText; resp_json=JSON.parse(resp) resp_place = document.getElementById("search_result_div") resp_place.innerHTML = resp_json['results'] search_meta = resp_json['meta'] update_search_meta(search_meta) update_pagination() hideLoading() } }; xhr.send(JSON.stringify(data)); } function unfilter() { url=/search_year_filter/ var term=document.getElementById("search_meta_data").dataset.term var data={ "year":"unfilter", "term":term, "pgn":1 } filtered_res=post_and_fetch(data,url) } function deactivate_all_bars(){ var yrchart = document.querySelectorAll('.ct-bar'); yrchart.forEach(function(bar) { bar.dataset.active = false bar.style = "stroke:#71a3c5;" }) } year_chart.on("created", function() { var yrchart = document.querySelectorAll('.ct-bar'); yrchart.forEach(function(check) { check.addEventListener('click', checkIndex); }) }); function checkIndex(event) { var yrchart = document.querySelectorAll('.ct-bar'); var year_bar = event.target if (year_bar.dataset.active == "true") { unfilter_res = unfilter() year_bar.dataset.active = false year_bar.style = "stroke:#1d2b3699;" } else { deactivate_all_bars() year_bar.dataset.active = true year_bar.style = "stroke:#e56f6f;" filter_year = chart_data['labels'][Array.from(yrchart).indexOf(year_bar)] url=/search_year_filter/ var term=document.getElementById("search_meta_data").dataset.term var data={ "year":filter_year, "term":term, "pgn":1 } filtered_res=post_and_fetch(data,url) } } function showLoading() { document.getElementById("loading").style.display = "block"; setTimeout(hideLoading, 10000); // 10 seconds } function hideLoading() { document.getElementById("loading").style.display = "none"; } -->