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| − | <script> | + | <!---------------- footer ---------------------> |
| | + | <script src="https://2019.igem.org/wiki/index.php?title=HQ:All_teams_info.js&action=raw&ctype=text/javascript"></script> |
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| − | $(document).ready(function() {
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| − |
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| − |
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| − | // all_teams_info
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| − | var all_teams_info = [
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| − | {
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| − | 'team_name':'Aachen',
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| − | 'wiki_link':'https://2018.igem.org/Team:Aachen',
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| − | 'location':'Germany',
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| − | 'institution':'RWTH Aachen University',
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| − | 'section':'Overgrad',
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| − | 'project_title':'Melasense',
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| − | 'track':'Diagnostics',
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| − | 'abstract':'We plan on developing a melatonin biosensor. Our approach for the biosensor is to genetically modify Saccharomyces cerevisiae by integrating a highly specific human melatonin receptor into the cells. Melatonin has a high membrane permeability which permits us to use the nuclear retinoid z receptor (RZR) which is directly regulating gene expression. We express the RZR as a fusion-protein with the recognition sequence of the human estrogen receptor alpha (ERα). When melatonin is bound.. the modified receptor binds to the estrogen receptor responsive element (ERE) and as a consequence regulate expression of firefly luciferase reporter genes. In our second approach.. we will use the membrane-receptor MT1 for our biosensor. When melatonin binds to the G protein-coupled receptor.. β-arrestins can be recruited. This mechanism allows us to use an enzyme fragment complementation assay based on two fusion-proteins.',
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| − | 'parts_link':'http://parts.igem.org/cgi/partsdb/pgroup.cgi?pgroup=iGEM2018&group=Aachen',
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| − | 'medal':'Gold',
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| − | 'nominations':'Best Hardware',
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| − | 'awards':''
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| − | },
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| − |
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| − | {
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| − | 'team_name':'Aalto-Helsinki',
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| − | 'wiki_link':'https://2018.igem.org/Team:Aalto-Helsinki',
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| − | 'location':'Finland',
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| − | 'institution':'Aalto University',
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| − | 'section':'Overgrad',
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| − | 'project_title':'Silkolor - A sustainable approach to dyeing industry using fusion proteins',
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| − | 'track':'New Application',
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| − | 'abstract':'Textile dyeing is one of the biggest polluters of natural waters. Many of the synthetic dyes used are non-biodegradable.. toxic and large amounts of them end up in waters during the dyeing process. Natural dyes.. although less toxic than synthetic ones.. require mordants in order to bind to the fabric. Mordants often contain aluminum or other metals.. which are harmful to the environment. We are addressing the problem by using two types of colorful fusion proteins. Chromoproteins are fused with binding domains to create colorful proteins which can bind cellulose or keratin based materials.. such as cotton or wool.. respectively. Spider silk is added to some of the proteins in order to make colored silk proteins that can be made into fibers.. which would erase the need for the dyeing step from the textile value chain completely. Our experiments were focused on binding tests and silk fiber production.',
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| − | 'parts_link':'http://parts.igem.org/cgi/partsdb/pgroup.cgi?pgroup=iGEM2018&group=Aalto-Helsinki',
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| − | 'medal':'Gold',
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| − | 'nominations':'Best Product Design',
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| − | 'awards':''
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| − | },
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| − |
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| − | {
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| − | 'team_name':'ACIBADEM ISTANBUL',
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| − | 'wiki_link':'https://2018.igem.org/Team:ACIBADEM_ISTANBUL',
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| − | 'location':'Turkey',
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| − | 'institution':'ACIBADEM UNIVERSITY',
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| − | 'section':'Undergrad',
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| − | 'project_title':'LTNF 2.0: Circularized Venom Neutralizing Factor',
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| − | 'track':'Therapeutics',
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| − | 'abstract':'The Opossum (Didelphimorphia) is an animal with a very unique characteristic; it displays an outstanding resistance to toxins.. snake venoms in particular. This anti-venom ability is gained through a single protein; the Lethal Toxin Neutralizing Factor (LTNF). We are attempting to produce an improved version of this anti-venom.. LTNF 2.0 if you will.. as a synthetic anti-venom for human use. LTNF 2.0 incorporates the post-translational modification process known as circularization.. a process that comprises of adding cysteine amino acids to both ends of a polypeptide chain; triggering the formation of a disulphide bridge.. ultimately leading to a circular structure.. hence the name circularization. Circularized proteins are known for not only greater stability but also greater efficacy of the protein.. thereby improving its shelf life and lowering the required dosage for treatment.. ultimately providing a more efficient bioproduct.',
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| − | 'parts_link':'http://parts.igem.org/cgi/partsdb/pgroup.cgi?pgroup=iGEM2018&group=ACIBADEM_ISTANBUL',
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| − | 'medal':'Bronze',
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| − | 'nominations':'',
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| − | 'awards':''
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| − | },
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| − |
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| − | {
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| − | 'team_name':'AFCM-Egypt',
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| − | 'wiki_link':'https://2018.igem.org/Team:AFCM-Egypt',
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| − | 'location':'Egypt',
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| − | 'institution':'Armed Forces College of Medicine',
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| − | 'section':'Overgrad',
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| − | 'project_title':'Microbiota: Opening Doors to New Horizons in Colorectal Cancer Therapy',
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| − | 'track':'Therapeutics',
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| − | 'abstract':'Colorectal cancer (CRC) is considered one of the most common cancers and accounts for almost half a million deaths annually worldwide. Tremendous progress has been made in understanding the role of the immune system in driving the development of cancers.. including CRC. As sensors of cell death and tissue remodeling.. Toll like receptors(TLRs) may have a universal role in cancer. There are different TLRs that respond to a variety of Pathogen associated molecular pattern (PAMPs) such as bacterial lipopolysaccharide . The evidence of existence of relevance between bacterial microbiota and carcinogenesis is increasing. it is suggested that microRNAs act as ligands of TLRs playing a role in epigenetic immune modulation. In this study.. We will assess the therapeutic efficacy of microbiome based approach as novel therapeutic strategy in restoring normal Toll lie receptor signaling in CRC cell line .',
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| − | 'parts_link':'http://parts.igem.org/cgi/partsdb/pgroup.cgi?pgroup=iGEM2018&group=AFCM-Egypt',
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| − | 'medal':'Silver',
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| − | 'nominations':'',
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| − | 'awards':''
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| − | }
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| − |
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| − |
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| − | ];
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| − |
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| − | //generate team and country list - once it is done, it calls the function to enable the search button
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| − | setup_teams_and_countries_list(all_teams_info);
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| − |
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| − |
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| − | //Place all the team information in the general printing div
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| − | for( x=0; x< all_teams_info.length; x++) {
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| − |
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| − | $("#general_printing").append("<div class='column half_size general_p'> <h2>" + all_teams_info[x].team_name +
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| − | "</h2> <p><b>Location:</b>" +all_teams_info[x].location+", "+all_teams_info[x].institution +
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| − | "<br><b>Section:</b>"+all_teams_info[x].section+
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| − | "<br><b>Track:</b>"+all_teams_info[x].track+
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| − | "</p><p><a href='"+all_teams_info[x].wiki_link+"'>"+all_teams_info[x].project_title+
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| − | "</a></p><p>"+all_teams_info[x].abstract+"</p></div>");
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| − |
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| − | //every two divs, clear to create spacing
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| − | if( (x%2) != 0 ){
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| − | $("#general_printing").append("<div class='clear extra_space'></div>");
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| − | }
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| − | }
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| − |
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| − |
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| − | //user is selecting something from the team list dropdown
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| − |
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| − | $( "#team_list" ).change(function() {
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| − |
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| − | //empty all previous results
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| − | $("#filtered_results").empty();
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| − |
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| − |
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| − | print_team($('#team_list').val(), all_teams_info);
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| − | });
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| − |
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| − |
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| − | //if a search is requested
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| − | $('#go_search_filter').click(function() {
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| − |
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| − | console.log("requesting a search");
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| − | search_request(all_teams_info);
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| − |
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| − | });
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| − |
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| − |
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| − |
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| − |
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| − | });
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| − |
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| − |
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| − | function setup_teams_and_countries_list(all_teams_info){
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| − |
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| − | var clean_name;
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| − |
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| − | //generate the team list
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| − | for (x=0; x< all_teams_info.length; x++){
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| − |
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| − | clean_name = (all_teams_info[x].team_name).replace(/ /g, "_");
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| − |
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| − | $("#team_list").append("<option value='"+clean_name+"'>"+all_teams_info[x].team_name+"</option>");
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| − |
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| − | }
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| − |
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| − | //clean the previous variable
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| − | clean_name = "";
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| − |
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| − | //generate the list of unique countries
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| − | var countries = [... new Set(all_teams_info.map(x => x.location))];
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| − |
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| − | for (x=0; x< countries.length; x++){
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| − |
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| − | clean_name = (countries[x]).replace(/ /g, "_");
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| − |
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| − | $("#country_list").append("<option value='"+clean_name+"'>"+countries[x]+"</option>");
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| − |
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| − | }
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| − |
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| − | //once the team and country list is done loading, enable the search button
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| − | console.log("done appending all the teams and countries ");
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| − | enable_search_button();
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| − | }
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| − |
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| − |
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| − |
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| − | //this is the main search and filter function
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| − | //searches by track, location,
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| − | function search_request(all_teams_info){
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| − |
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| − | //empty all previous results
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| − |
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| − | $("#filtered_results").empty();
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| − |
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| − | //variable to check if the search can be done
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| − | var proper_search = true;
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| − |
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| − | //create a temp object for searching
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| − | var temp_object ={};
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| − |
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| − | //get the values to search for each category
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| − | var values_to_search = {
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| − | location: $('#country_list').val(),
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| − | track: $('#track_list').val(),
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| − | section: $('#section_list').val()
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| − | };
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| − |
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| − | console.log("searching for the following values:"+values_to_search.location+" "+values_to_search.track+" "+values_to_search.section);
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| − |
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| − |
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| − | // if the user hasn't selected any particular category, ask them to narrow down the search
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| − | if(values_to_search.location == 'all'){
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| − | if(values_to_search.track == 'all'){
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| − | if(values_to_search.section =='all'){
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| − | console.log("narrow your search, please");
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| − | $("#filtered_results").append("<p>Please narrow down your search.</p>");
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| − | proper_search = false ;
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| − | }
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| − | }
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| − | }
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| − |
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| − |
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| − | if(proper_search == true){
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| − |
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| − |
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| − | for (x=0; x< all_teams_info.length; x++){
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| − |
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| − | //populate temp object with current team
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| − | temp_object = all_teams_info[x];
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| − |
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| − | /**
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| − | //check for country
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| − | if( temp_object.location == values_to_search.location ){
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| − | console.log("Found instance of: "+values_to_search.location+" -in team- "+ temp_object.team_name );
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| − | $("#filtered_results").append("<p>Found:"+ temp_object.team_name+"</p>");
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| − | }
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| − |
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| − | //check for track
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| − | if( temp_object.track == values_to_search.track ){
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| − | console.log("Found instance of: "+values_to_search.track+" -in team- "+ temp_object.team_name );
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| − | $("#filtered_results").append("<p>Found:"+ temp_object.team_name+"</p>");
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| − | }
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| − |
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| − |
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| − | //check for section
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| − | if( temp_object.section == values_to_search.section){
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| − | console.log("Found instance of: "+values_to_search.section+" -in team- "+ temp_object.team_name );
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| − | $("#filtered_results").append("<p>Found:"+ temp_object.team_name+"</p>");
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| − | }
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| − | **/
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| − |
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| − |
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| − | //decision tree to figure out what variable combinations the user is requesting
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| − | if(values_to_search.location != 'all'){
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| − |
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| − | console.log("user chose a location");
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| − |
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| − | if(values_to_search.track != 'all'){
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| − |
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| − | console.log("user chose a track");
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| − |
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| − | if(values_to_search.section != 'all'){
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| − |
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| − | console.log("user chose a section");
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| − |
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| − | }
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| − | else{
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| − | console.log("user didnt chose a section");
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| − | }
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| − |
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| − | }
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| − | else{
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| − | console.log("user didnt chose a track");
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| − |
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| − | if(values_to_search.section != 'all'){
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| − |
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| − | console.log("user chose a section");
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| − |
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| − | }
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| − | else{
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| − | console.log("user didnt chose a section");
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| − | }
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| − | }
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| − |
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| − |
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| − | }
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| − |
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| − | else{
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| − | console.log("user didnt chose a location");
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| − |
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| − | if(values_to_search.track != 'all'){
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| − |
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| − | console.log("user chose a track");
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| − |
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| − | if(values_to_search.section != 'all'){
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| − |
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| − | console.log("user chose a section");
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| − |
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| − | }
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| − | else{
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| − | console.log("user didnt chose a section");
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| − | }
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| − |
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| − | }
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| − | else{
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| − | console.log("user didnt chose a track");
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| − |
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| − | if(values_to_search.section != 'all'){
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| − |
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| − | console.log("user chose a section");
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| − |
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| − | }
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| − | else{
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| − | console.log("user didnt chose a section");
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| − | }
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| − | }
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| − | }
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| − |
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| − |
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| − |
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| − | }
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| − | }
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| − |
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| − |
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| − | }
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| − |
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| − |
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| − | function print_team(team_name, all_teams_info){
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| − |
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| − | var temp_clean_name;
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| − |
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| − | for (x=0; x< all_teams_info.length; x++){
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| − |
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| − | temp_clean_name = (all_teams_info[x].team_name).replace(/ /g, "_");
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| − |
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| − | if(team_name == temp_clean_name) {
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| − |
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| − | $("#filtered_results").append("<div class='column full_size general_p'> <h2>" + all_teams_info[x].team_name +
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| − | "</h2> <p><b>Location:</b>" +all_teams_info[x].location+", "+all_teams_info[x].institution +
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| − | "<br><b>Section:</b>"+all_teams_info[x].section+
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| − | "<br><b>Track:</b>"+all_teams_info[x].track+
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| − | "</p><p><a href='"+all_teams_info[x].wiki_link+"'>"+all_teams_info[x].project_title+
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| − | "</a></p><p>"+all_teams_info[x].abstract+"</p></div>");
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| − |
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| − | }
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| − | }
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| − | }
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| − |
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| − |
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| − | function enable_search_button(){
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| − |
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| − | $("#go_search_filter").removeClass("button_disabled");
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| − | console.log("The search button is now enabled");
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| − | }
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| − |
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| − |
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| − | </script>
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| | </html> | | </html> |
| | {{Footer2019}} | | {{Footer2019}} |
