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zeromtmu's Projects

csb icon csb

Material for Computing Skills for Biologists

dash icon dash

Interactive, reactive web apps in pure python :level_slider: :bar_chart:

data-science-ipython-notebooks icon data-science-ipython-notebooks

Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.

dcell icon dcell

DCell browser and gene deletion simulator

deepchem icon deepchem

Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology

deepcut icon deepcut

A Thai word tokenization library using Deep Neural Network

deepsea icon deepsea

Similarity Ensemble Approach with deep learning substance fingerprints

detectdesign icon detectdesign

toolkit for finding likely cas9 off-target binding and effect on gene expression, designing sgRNAs and pairs of sgRNAs with minimal off-target effect on gene-expression

dimpyplot icon dimpyplot

A Python frontend to the LigPlot+ program, allowing batch processing of Protein Data Bank (PDB) files through the DIMPLOT algorithm.

djiastats icon djiastats

Wikipedia page views plotted against stock metrics.

docking-scripts icon docking-scripts

Scripts used for virtual screening of small molecule inhibitors from ZINC database using Autodock Vina

e3fp icon e3fp

3D molecular fingerprints

ehr-phenolyzer icon ehr-phenolyzer

A pipeline that takes clinical notes from EHRs and generate phenotype terms, then generate ranked gene list

explore-uniprotkb-with-amazon-neptune icon explore-uniprotkb-with-amazon-neptune

In this example, we will demonstrate the step-by-step process to create and use your own protein knowledge base using UniProt RDF data. We will show how to ingest a subset of UniProtKB data into your own Amazon Neptune database directly from the Registry of Open Data on AWS. We will then show how to query the data with SPARQL, create new relationships in the data and visualise the data as a graph.

gatk_pipeline icon gatk_pipeline

Pipeline for processing raw fastq files through SNP calling with GATK and subsequent filtering

gdynet icon gdynet

Unsupervised learning of atomic scale dynamics from molecular dynamics.

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