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Relay

Autonomous relay system for NCATS Biomedical Data Translator

The ARS will:

  • Relay the query from the user to the ARAs​
  • Use an iterative process with the ARAs to generate the result in the form of a knowledge graph provided to the user​
  • The goal of iterating with ARAs is to fill gaps, “clean up” a graph, enrich the graph, etc.​

The ARS can:

  • Decide which ARAs to invoke​
  • Rank and score answers as being most correct/relevant to the user's query​

The ARS does not:

  • Gatekeep. Behavior will be deterministic based on published process/rules.​
  • Do ETL. Answers received from the ARAs should already be in compliance with standards. ​
  • Interact directly with users; there will be an interface for that.​

Communication between the ARS and other Translator tools will be based on a Publish/Subscribe model​

ARS will assign 'topics' to a query (or parts) it receives. These topics might include: genes, clinical data, drugs, or pathways. The ARS publishes to these topics. Translator tools able to handle queries related to the topics respond. The ARS invokes tools that responded to the topics. When a tool subscribes to a channel (like genes or drugs), it will be notified when anything is posted there (like a query involving those topics) and can choose how to respond.

Deploy

See to the tr_sys folder for deployment instructions.

Register a service

Documentation can be found here

About

Autonomous relay system for NCATS Biomedical Data Translator

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Readme
MIT license
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, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Add copy buttons to all 
 blocks\n(function() {\n function addCopyButtons() {\n document.querySelectorAll('pre code').forEach(function(codeBlock) {\n if (codeBlock.parentElement.hasAttribute('data-copy-added')) return;\n codeBlock.parentElement.setAttribute('data-copy-added', 'true');\n \n var btn = document.createElement('button');\n btn.textContent = 'Copy';\n btn.style.cssText = 'position:absolute;top:4px;right:4px;padding:2px 8px;font-size:11px;background:#4ecdc4;border:none;border-radius:4px;color:#1a1a2e;cursor:pointer;opacity:0.7;transition:opacity 0.2s;';\n btn.onmouseover = function() { this.style.opacity = '1'; };\n btn.onmouseout = function() { this.style.opacity = '0.7'; };\n btn.onclick = function() {\n navigator.clipboard.writeText(codeBlock.textContent).then(function() {\n btn.textContent = 'Copied!';\n setTimeout(function() { btn.textContent = 'Copy'; }, 1500);\n });\n };\n codeBlock.parentElement.style.position = 'relative';\n codeBlock.parentElement.appendChild(btn);\n });\n }\n \n addCopyButtons();\n \n // Re-run on dynamic content\n var observer = new MutationObserver(addCopyButtons);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Add Copy Buttons to Code Blocks");
}
} catch(__e) { console.warn('[Userscript:Add Copy Buttons to Code Blocks]', __e); }
})();
(function(){
try {
var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '

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BranchesTags
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Relay
Autonomous relay system for NCATS Biomedical Data Translator
The ARS will:
  • Relay the query from the user to the ARAs​
  • Use an iterative process with the ARAs to generate the result in the form of a knowledge graph provided to the user​
  • The goal of iterating with ARAs is to fill gaps, “clean up” a graph, enrich the graph, etc.​
The ARS can:
  • Decide which ARAs to invoke​
  • Rank and score answers as being most correct/relevant to the user's query​
The ARS does not:
  • Gatekeep. Behavior will be deterministic based on published process/rules.​
  • Do ETL. Answers received from the ARAs should already be in compliance with standards. ​
  • Interact directly with users; there will be an interface for that.​
Communication between the ARS and other Translator tools will be based on a Publish/Subscribe model​
ARS will assign 'topics' to a query (or parts) it receives. These topics might include: genes, clinical data, drugs, or pathways. The ARS publishes to these topics. Translator tools able to handle queries related to the topics respond. The ARS invokes tools that responded to the topics. When a tool subscribes to a channel (like genes or drugs), it will be notified when anything is posted there (like a query involving those topics) and can choose how to respond.
Deploy
See to the tr_sys folder for deployment instructions.
Register a service
Documentation can be found here
About
Autonomous relay system for NCATS Biomedical Data Translator
Resources
Readme
MIT license
Activity
Stars
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0 watching
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0 forks
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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Force GitHub README to respect dark mode\n(function() {\n var style = document.createElement('style');\n style.textContent = '\n .markdown-body {\n color-scheme: dark light;\n }\n .markdown-body pre { background: #161b22 !important; }\n .markdown-body code { background: rgba(110, 118, 129, 0.4) !important; }\n .markdown-body table th, .markdown-body table td { border-color: #30363d !important; }\n .markdown-body img { background: #0d1117; }\n .markdown-body blockquote { border-left-color: #8b949e; }\n .markdown-body hr { border-color: #30363d; }\n ';\n document.head.appendChild(style);\n})();", "GitHub Dark Mode README Fix");
}
} catch(__e) { console.warn('[Userscript:GitHub Dark Mode README Fix]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
BranchesTags
Repository files navigation
Relay
Autonomous relay system for NCATS Biomedical Data Translator
The ARS will:
  • Relay the query from the user to the ARAs​
  • Use an iterative process with the ARAs to generate the result in the form of a knowledge graph provided to the user​
  • The goal of iterating with ARAs is to fill gaps, “clean up” a graph, enrich the graph, etc.​
The ARS can:
  • Decide which ARAs to invoke​
  • Rank and score answers as being most correct/relevant to the user's query​
The ARS does not:
  • Gatekeep. Behavior will be deterministic based on published process/rules.​
  • Do ETL. Answers received from the ARAs should already be in compliance with standards. ​
  • Interact directly with users; there will be an interface for that.​
Communication between the ARS and other Translator tools will be based on a Publish/Subscribe model​
ARS will assign 'topics' to a query (or parts) it receives. These topics might include: genes, clinical data, drugs, or pathways. The ARS publishes to these topics. Translator tools able to handle queries related to the topics respond. The ARS invokes tools that responded to the topics. When a tool subscribes to a channel (like genes or drugs), it will be notified when anything is posted there (like a query involving those topics) and can choose how to respond.
Deploy
See to the tr_sys folder for deployment instructions.
Register a service
Documentation can be found here
About
Autonomous relay system for NCATS Biomedical Data Translator
Resources
Readme
MIT license
Activity
Stars
0 stars
Watchers
0 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Highlight search terms from Google/DuckDuckGo/Bing referrer\n(function() {\n var ref = document.referrer;\n var terms = [];\n \n if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {\n var url = new URL(ref);\n var q = url.searchParams.get('q') || url.searchParams.get('p');\n if (q) {\n terms = q.split(/\\s+/).filter(function(t) { return t.length > 2; });\n }\n }\n \n if (terms.length === 0) return;\n \n var style = document.createElement('style');\n style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';\n document.head.appendChild(style);\n \n function highlight(node) {\n if (node.nodeType === 3) { // text node\n var text = node.textContent;\n var found = false;\n terms.forEach(function(term) {\n var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\\]\\\\]/g, '\\\\') + ')', 'gi');\n if (regex.test(text)) {\n found = true;\n var frag = document.createDocumentFragment();\n var parts = text.split(regex);\n parts.forEach(function(part, i) {\n if (i % 2 === 0) {\n frag.appendChild(document.createTextNode(part));\n } else {\n var span = document.createElement('span');\n span.className = 'userscript-highlight';\n span.textContent = part;\n frag.appendChild(span);\n }\n });\n node.parentNode.replaceChild(frag, node);\n }\n });\n } else if (node.nodeType === 1 && node.childNodes) { // element\n var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT'];\n if (!skipTags.includes(node.tagName)) {\n Array.from(node.childNodes).forEach(highlight);\n }\n }\n }\n \n highlight(document.body);\n \n // Re-highlight on dynamic content\n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1 || node.nodeType === 3) highlight(node);\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Highlight Search Terms");
}
} catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
BranchesTags
Repository files navigation
Relay
Autonomous relay system for NCATS Biomedical Data Translator
The ARS will:
  • Relay the query from the user to the ARAs​
  • Use an iterative process with the ARAs to generate the result in the form of a knowledge graph provided to the user​
  • The goal of iterating with ARAs is to fill gaps, “clean up” a graph, enrich the graph, etc.​
The ARS can:
  • Decide which ARAs to invoke​
  • Rank and score answers as being most correct/relevant to the user's query​
The ARS does not:
  • Gatekeep. Behavior will be deterministic based on published process/rules.​
  • Do ETL. Answers received from the ARAs should already be in compliance with standards. ​
  • Interact directly with users; there will be an interface for that.​
Communication between the ARS and other Translator tools will be based on a Publish/Subscribe model​
ARS will assign 'topics' to a query (or parts) it receives. These topics might include: genes, clinical data, drugs, or pathways. The ARS publishes to these topics. Translator tools able to handle queries related to the topics respond. The ARS invokes tools that responded to the topics. When a tool subscribes to a channel (like genes or drugs), it will be notified when anything is posted there (like a query involving those topics) and can choose how to respond.
Deploy
See to the tr_sys folder for deployment instructions.
Register a service
Documentation can be found here
About
Autonomous relay system for NCATS Biomedical Data Translator
Resources
Readme
MIT license
Activity
Stars
0 stars
Watchers
0 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Strip utm_, fbclid, gclid, etc. from all links on page\n(function() {\n var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',\n 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',\n 'ref', 'ref_src', 'source', 'medium', 'campaign'];\n \n function cleanUrl(url) {\n try {\n var u = new URL(url, window.location.origin);\n var changed = false;\n trackingParams.forEach(function(p) {\n if (u.searchParams.has(p)) {\n u.searchParams.delete(p);\n changed = true;\n }\n });\n return changed ? u.toString() : url;\n } catch (e) {\n return url;\n }\n }\n \n function cleanLinks() {\n document.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n \n cleanLinks();\n \n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1) {\n if (node.tagName === 'A') cleanLinks();\n node.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Remove Tracking Parameters from Links");
}
} catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); }
})();
(function(){
try {
var __m = "youtube.com";
var __re = new RegExp('^' + "youtube\\.com" + '

Skip to content
BranchesTags
Repository files navigation
Relay
Autonomous relay system for NCATS Biomedical Data Translator
The ARS will:
  • Relay the query from the user to the ARAs​
  • Use an iterative process with the ARAs to generate the result in the form of a knowledge graph provided to the user​
  • The goal of iterating with ARAs is to fill gaps, “clean up” a graph, enrich the graph, etc.​
The ARS can:
  • Decide which ARAs to invoke​
  • Rank and score answers as being most correct/relevant to the user's query​
The ARS does not:
  • Gatekeep. Behavior will be deterministic based on published process/rules.​
  • Do ETL. Answers received from the ARAs should already be in compliance with standards. ​
  • Interact directly with users; there will be an interface for that.​
Communication between the ARS and other Translator tools will be based on a Publish/Subscribe model​
ARS will assign 'topics' to a query (or parts) it receives. These topics might include: genes, clinical data, drugs, or pathways. The ARS publishes to these topics. Translator tools able to handle queries related to the topics respond. The ARS invokes tools that responded to the topics. When a tool subscribes to a channel (like genes or drugs), it will be notified when anything is posted there (like a query involving those topics) and can choose how to respond.
Deploy
See to the tr_sys folder for deployment instructions.
Register a service
Documentation can be found here
About
Autonomous relay system for NCATS Biomedical Data Translator
Resources
Readme
MIT license
Activity
Stars
0 stars
Watchers
0 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Auto-enable theater mode on YouTube\n(function() {\n function tryTheater() {\n var btn = document.querySelector('button[aria-label=\"Theater mode\"], ytd-player #player button[title=\"Theater mode\"]');\n if (btn && !btn.classList.contains('activated')) {\n btn.click();\n }\n }\n \n // Try immediately\n tryTheater();\n \n // Try after navigation (SPA)\n var lastUrl = location.href;\n setInterval(function() {\n if (location.href !== lastUrl) {\n lastUrl = location.href;\n setTimeout(tryTheater, 500);\n }\n }, 1000);\n \n // Also try on player load\n var observer = new MutationObserver(tryTheater);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "YouTube Theater Mode Default");
}
} catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
BranchesTags
Repository files navigation
Relay
Autonomous relay system for NCATS Biomedical Data Translator
The ARS will:
  • Relay the query from the user to the ARAs​
  • Use an iterative process with the ARAs to generate the result in the form of a knowledge graph provided to the user​
  • The goal of iterating with ARAs is to fill gaps, “clean up” a graph, enrich the graph, etc.​
The ARS can:
  • Decide which ARAs to invoke​
  • Rank and score answers as being most correct/relevant to the user's query​
The ARS does not:
  • Gatekeep. Behavior will be deterministic based on published process/rules.​
  • Do ETL. Answers received from the ARAs should already be in compliance with standards. ​
  • Interact directly with users; there will be an interface for that.​
Communication between the ARS and other Translator tools will be based on a Publish/Subscribe model​
ARS will assign 'topics' to a query (or parts) it receives. These topics might include: genes, clinical data, drugs, or pathways. The ARS publishes to these topics. Translator tools able to handle queries related to the topics respond. The ARS invokes tools that responded to the topics. When a tool subscribes to a channel (like genes or drugs), it will be notified when anything is posted there (like a query involving those topics) and can choose how to respond.
Deploy
See to the tr_sys folder for deployment instructions.
Register a service
Documentation can be found here
About
Autonomous relay system for NCATS Biomedical Data Translator
Resources
Readme
MIT license
Activity
Stars
0 stars
Watchers
0 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Remove or un-stick sticky/fixed headers that block content\n(function() {\n function unstick() {\n document.querySelectorAll('header, nav, [role=\"banner\"], .header, .navbar, .sticky, .fixed-top, [style*=\"position: fixed\"], [style*=\"position:sticky\"]').forEach(function(el) {\n if (el.style.position === 'fixed' || el.style.position === 'sticky' || \n getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {\n el.style.position = 'static';\n el.style.top = 'auto';\n el.style.zIndex = 'auto';\n }\n });\n }\n \n unstick();\n \n var observer = new MutationObserver(unstick);\n observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });\n})();", "Kill Sticky Headers");
}
} catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
BranchesTags
Repository files navigation
Relay
Autonomous relay system for NCATS Biomedical Data Translator
The ARS will:
  • Relay the query from the user to the ARAs​
  • Use an iterative process with the ARAs to generate the result in the form of a knowledge graph provided to the user​
  • The goal of iterating with ARAs is to fill gaps, “clean up” a graph, enrich the graph, etc.​
The ARS can:
  • Decide which ARAs to invoke​
  • Rank and score answers as being most correct/relevant to the user's query​
The ARS does not:
  • Gatekeep. Behavior will be deterministic based on published process/rules.​
  • Do ETL. Answers received from the ARAs should already be in compliance with standards. ​
  • Interact directly with users; there will be an interface for that.​
Communication between the ARS and other Translator tools will be based on a Publish/Subscribe model​
ARS will assign 'topics' to a query (or parts) it receives. These topics might include: genes, clinical data, drugs, or pathways. The ARS publishes to these topics. Translator tools able to handle queries related to the topics respond. The ARS invokes tools that responded to the topics. When a tool subscribes to a channel (like genes or drugs), it will be notified when anything is posted there (like a query involving those topics) and can choose how to respond.
Deploy
See to the tr_sys folder for deployment instructions.
Register a service
Documentation can be found here
About
Autonomous relay system for NCATS Biomedical Data Translator
Resources
Readme
MIT license
Activity
Stars
0 stars
Watchers
0 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Universal Dark Mode - works on any site\n(function() {\n var enabled = true;\n \n function applyDarkMode() {\n if (!enabled) return;\n \n // Create style element if it doesn't exist\n var style = document.getElementById('universal-dark-mode-style');\n if (!style) {\n style = document.createElement('style');\n style.id = 'universal-dark-mode-style';\n document.head.appendChild(style);\n }\n \n // Dark mode CSS - inverts colors but preserves images/video\n style.textContent = '\n /* Invert everything except media */\n html {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #1a1a2e !important;\n }\n \n /* Restore images, videos, iframes, canvas */\n img, video, iframe, canvas, svg, picture, [style*=\"background-image\"] {\n filter: invert(1) hue-rotate(180deg) !important;\n }\n \n /* Preserve specific elements that should not be inverted */\n .no-dark-mode, .no-dark-mode *,\n [data-theme=\"light\"], [data-theme=\"light\"],\n .ace_editor, .ace_editor *,\n .CodeMirror, .CodeMirror *,\n .monaco-editor, .monaco-editor *,\n .markdown-body pre, .markdown-body pre *,\n .highlight, .highlight *,\n pre code, pre code * {\n filter: none !important;\n }\n \n /* Fix common UI elements */\n .modal, .popup, .dropdown-menu, .tooltip, .popover {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #2d2d44 !important;\n border-color: #444 !important;\n }\n \n /* Scrollbars */\n ::-webkit-scrollbar { background: #1a1a2e !important; }\n ::-webkit-scrollbar-thumb { background: #444 !important; }\n ::-webkit-scrollbar-thumb:hover { background: #555 !important; }\n \n /* Selection */\n ::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ';\n }\n \n function removeDarkMode() {\n var style = document.getElementById('universal-dark-mode-style');\n if (style) style.remove();\n }\n \n // Toggle with Alt+Shift+D\n document.addEventListener('keydown', function(e) {\n if (e.altKey && e.shiftKey && e.key === 'D') {\n e.preventDefault();\n enabled = !enabled;\n if (enabled) {\n applyDarkMode();\n console.log('[Universal Dark Mode] Enabled');\n } else {\n removeDarkMode();\n console.log('[Universal Dark Mode] Disabled');\n }\n }\n });\n \n // Apply on load\n applyDarkMode();\n \n // Re-apply on dynamic content\n var observer = new MutationObserver(function(mutations) {\n if (enabled && !document.getElementById('universal-dark-mode-style')) {\n applyDarkMode();\n }\n });\n observer.observe(document.head, { childList: true });\n \n console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');\n})();", "Universal Dark Mode");
}
} catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); }
})();
})();

Skip to content
BranchesTags
Repository files navigation
Relay
Autonomous relay system for NCATS Biomedical Data Translator
The ARS will:
  • Relay the query from the user to the ARAs​
  • Use an iterative process with the ARAs to generate the result in the form of a knowledge graph provided to the user​
  • The goal of iterating with ARAs is to fill gaps, “clean up” a graph, enrich the graph, etc.​
The ARS can:
  • Decide which ARAs to invoke​
  • Rank and score answers as being most correct/relevant to the user's query​
The ARS does not:
  • Gatekeep. Behavior will be deterministic based on published process/rules.​
  • Do ETL. Answers received from the ARAs should already be in compliance with standards. ​
  • Interact directly with users; there will be an interface for that.​
Communication between the ARS and other Translator tools will be based on a Publish/Subscribe model​
ARS will assign 'topics' to a query (or parts) it receives. These topics might include: genes, clinical data, drugs, or pathways. The ARS publishes to these topics. Translator tools able to handle queries related to the topics respond. The ARS invokes tools that responded to the topics. When a tool subscribes to a channel (like genes or drugs), it will be notified when anything is posted there (like a query involving those topics) and can choose how to respond.
Deploy
See to the tr_sys folder for deployment instructions.
Register a service
Documentation can be found here
About
Autonomous relay system for NCATS Biomedical Data Translator
Resources
Readme
MIT license
Activity
Stars
0 stars
Watchers
0 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
Languages