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Design a local part of a protein
A high-quality hand-curated logD7.4 dataset of 1,130 compounds
Windows tail program and log file analyzer.
R Interface to 'Lp_solve' v. 5.5 to Solve Linear/Integer Programs
LSA: a local-weighted structure alignment tool for pharmaceutical virtual screening
Large-scale comparison of machine learning methods for drug target prediction on ChEMBL
Locality Sensitive Hashing In R
Implementation of the paper - Generative Recurrent Networks for De Novo Drug Design.
Long short-term memory recurrent neural networks for learning peptide and protein sequences to later design new, similar examples.
Single-cell Lung Cancer Atlas with 1.2M cells
Some code related to "Learning by Unsupervised Nonlinear Diffusion" by Maggioni and Murphy (JMLR 2020).
Layered Chemical Identifier
Retrosynthesis has been used for a long time, but it's slower and prone to bias. Machine learning aided techniques like this can help speed up the process.
A resource for learning about Machine learning & Deep Learning
Multi-layer perceptron model for photo-voltaic material properties prediction.
Listing of papers about machine learning for proteins.
Transition metal oxides are attractive materials for high temperature thermoelectric applications due to their thermal stability, low cost bulk processing and natural abundance. Notwithstanding the high power factor, their high thermal conductivity is a roadblock in achieving higher efficiency. The search space for new thermoelectric oxides has been limited to the alloys of a few previously explored systems, such as ZnO, SrTiO3 and CaMnO3. The phenomenon of thermal conduction in crystalline alloys and its dependence on crystal properties is also poorly understood, which limits the ability to design new alloys. In this paper, we apply machine-learning models for discovering novel transition metal oxides with low lattice thermal conductivity (kL). A two-step process is proposed to address the problem of small datasets frequently encountered in materials informatics. First, a gradient boosted tree classifier is learnt to categorize unknown compounds into three categories of thermal conductivity: Low, Medium, and High. In the second step, we fit regression models on the targeted class (i.e. low kL) to estimate kL with an R2 value of 0.96. Gradient boosted tree model was also used to identify key material properties influencing classification of kL, namely lattice energy per atom, atom density, electronic energy band gap, mass density, and ratio of oxygen by transition metal atoms. Only fundamental materials properties describing the crystal symmetry, compound chemistry and interatomic bonding were used in the classification process, which can be readily used as selection parameters. The proposed two-step process addresses the problem of small datasets and improves the predictive accuracy.
Machine Learning Interviews from FAANG, Snapchat, LinkedIn. I have offers from Snapchat, Coupang, Stitchfix etc. Blog: mlengineer.io.
Using multiple machine learning algorithms to generate the best predicitive model for the degree of solubility of a chemical compound given its molecular formula.
Aqueous solubility prediction
Machine learning and artificial intelligence
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.