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diff --git a/docs/posts/2021-06-26-Cheminformatics-On-The-Web-2021.html b/docs/posts/2021-06-26-Cheminformatics-On-The-Web-2021.html index 885c7b5..3324928 100644 --- a/docs/posts/2021-06-26-Cheminformatics-On-The-Web-2021.html +++ b/docs/posts/2021-06-26-Cheminformatics-On-The-Web-2021.html @@ -41,24 +41,21 @@ <main> <h1>Cheminformatics on the Web (2021)</h1> -<p>Here, I have compiled a list of some tools and possible solutions. -The web is a nice platform, it is available anywhere and just requires an internet connection. -I, personally like static websites which don't require a server side application and can be hosted on platforms like GitHub Pages. -Or, just open the HTML file and run it in your browser. -No data is required to be sent to any server and your device's computational power is used. -Even our phones have a lot of computational power now, which allows the user to run tasks on the go without needing to worry about managing dependencies. -WebAssembly (Wasm) has made running code written for other platfroms on the web relativevly easier. +<p>Here, I have compiled a list of some libraries and possible ideas. +I, personally, like static websites which don't require a server side application and can be hosted on platforms like GitHub Pages. +Or, just by opening the HTML file and running it in your browser. +WebAssembly (Wasm) has made running code written for other platforms on the web relatively easier. Combine Wasm with some pure JavaScript libraries, and you get a platform to quickly amp up your speed in some common tasks.</p> <h2>RDKit</h2> <p>RDKit bundles a minimal JavaScript Wrapper in their core RDKit suite. -This is perfect for generating 2D Figures (HTML5 Canva/SVGs), Cannonical SMILES, Descriptors e.t.c</p> +This is perfect for generating 2D Figures (HTML5 Canva/SVGs), Canonical SMILES, Descriptors e.t.c</p> <h3>Substructure Matching</h3> <p>This can be used to flag undesirable functional groups in a given compound. -Create a simple key:value pair of name:SMARTS and use it to highlight substructure matches. +Create a simple key:value pairs of name:SMARTS and use it to highlight substructure matches. Thus, something like PostEra's Medicinal Chemistry Alert can be done with RDKit-JS alone.</p> <p><img src="/assets/posts/cheminformatics-web/postera-demo.png" alt="PostEra Demo" /></p> @@ -78,22 +75,22 @@ Thus, something like PostEra's Medicinal Chemistry Alert can be done with RDKit- <p>Obviously, it takes a few hits in the time to complete the docking because the code is transpiled from C++ to Wasm. But, the only major drawback (for now) is that it uses SharedArrayBuffer. Due to Spectre, this feature was disabled on all browsers. -Currently, only Chromium-based and Firefox browsers have reimplemented and renabled it. -Hopefully, soon this will be again supported by all major browsers.</p> +Currently, only Chromium-based and Firefox browsers have reimplemented and enabled it. +Hopefully, soon, this will be again supported by all major browsers.</p> <h2>Machine Learning</h2> <p>Frameworks have now evolved enough to allow exporting models to be able to run them through JavaScript/Wasm backend. An example task can be <strong>NER</strong> or Named-entity Recognition. -It can be used to extract compounds or diseases from a large blob of text and then matched with external refferences. +It can be used to extract compounds or diseases from a large blob of text and then matched with external references. Another example is target-prediction right in the browser: <a rel="noopener" target="_blank" href="http://chembl.blogspot.com/2021/03/target-predictions-in-browser-with.html">CHEMBL - Target Prediction in Browser</a></p> <p>CHEMBL Group is first training the model using PyTorch (A Python ML Library), then converting it to the ONNX runtime. -A model like this can be directly implemented in Tensorflow, and then exported to be able to run with TensorFlow.js</p> +A model like this can be directly implemented in TensorFlow, and then exported to be able to run with TensorFlow.js</p> <h2>Cheminfo-to-web</h2> -<p>The project aims to port chemoinformatics libraries into JavaScript via Emscripten. +<p>The project aims to port cheminformatics libraries into JavaScript via Emscripten. They have ported InChI, Indigo, OpenBabel, and OpenMD</p> <h3>Kekule.js</h3> @@ -108,7 +105,7 @@ They have ported InChI, Indigo, OpenBabel, and OpenMD</p> <p>The previous machine learning examples can be packaged as browser-extensions to perform tasks on the article you are reading. With iOS 15 bringing WebExtensions to iOS/iPadOS, the same browser extension source code can be now used on Desktop and Mobile Phones. -You can quickly create an extenison to convert PDB codes into links to RCSB, highlight SMILES, highlight output of NER models, e.t.c</p> +You can quickly create an extension to convert PDB codes into links to RCSB, highlight SMILES, highlight output of NER models, e.t.c</p> <h2>Conclusion</h2> |