نتایج جستجو برای: codon preference optimization

تعداد نتایج: 401777  

Journal: :PLoS ONE 2008
Fiona Robinson Richard J. Jackson Christopher W. J. Smith

BACKGROUND The frequency of synonymous codon usage varies widely between organisms. Suboptimal codon content limits expression of viral, experimental or therapeutic heterologous proteins due to limiting cognate tRNAs. Codon content is therefore often adjusted to match codon bias of the host organism. Codon content also varies between genes within individual mammalian species. However, little at...

2003
Ronen I. Brafman Yannis Dimopoulos

Preference elicitation is a serious bottleneck in many decision support applications and agent specification tasks. CP-nets were designed to make the preference elicitation process simpler and more intuitive for lay users by graphically structuring a set of Ceteris Paribus (CP) preference statements preference statements most people find natural and intuitive. In various contexts, CP-nets with ...

Journal: :J. Artif. Intell. Res. 2006
Ronen I. Brafman Carmel Domshlak Solomon Eyal Shimony

In recent years, CP-nets have emerged as a useful tool for supporting preference elicitation, reasoning, and representation. CP-nets capture and support reasoning with qualitative conditional preference statements, statements that are relatively natural for users to express. In this paper, we extend the CP-nets formalism to handle another class of very natural qualitative statements one often u...

Journal: :Front. Robotics and AI 2018
Paolo Dragone Stefano Teso Andrea Passerini

When faced with large or complex decision problems, human decision makers (DM) can make costly mistakes, due to inherent limitations of their memory, attention, and knowledge. Preference elicitation tools assist the decision maker in overcoming these limitations. They do so by interactively learning the DM’s preferences through appropriately chosen queries and suggesting high-quality outcomes b...

Journal: :BioSystems 2021

The X circular code is a set of 20 trinucleotides (codons) that has been identified in the protein-coding genes most organisms (bacteria, archaea, eukaryotes, plasmids, viruses). It shown previously important mathematical property being an error-correcting code. Thus, motifs code, i.e. series codons belonging to and called motifs, allow identification maintenance reading frame genes. are signif...

1995
Kannan Govindarajan Bharat Jayaraman Surya Mantha

Optimization and relaxation are two important operations that naturally arise in many applications requiring the use of constraints, e.g., engineering design, scheduling, decision support, etc. In optimization , we are interested in nding the optimal solutions to a set of constraints with respect to an objective function. In many applications, optimal solutions may be diicult or impossible to o...

پایان نامه :دانشگاه آزاد اسلامی - دانشگاه آزاد اسلامی واحد تهران مرکزی - دانشکده برق و الکترونیک 1390

there are many approaches for solving variety combinatorial optimization problems (np-compelete) that devided to exact solutions and approximate solutions. exact methods can only be used for very small size instances due to their expontional search space. for real-world problems, we have to employ approximate methods such as evolutionary algorithms (eas) that find a near-optimal solution in a r...

Journal: :Gene 2005
Yizhar Lavner Daniel Kotlar

We study the interrelations between tRNA gene copy numbers, gene expression levels and measures of codon bias in the human genome. First, we show that isoaccepting tRNA gene copy numbers correlate positively with expression-weighted frequencies of amino acids and codons. Using expression data of more than 14,000 human genes, we show a weak positive correlation between gene expression level 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"; } -->