amsyuan

amsyuan's Stars

• lucidrains/progen

  Implementation and replication of ProGen, Language Modeling for Protein Generation, in Jax

  Language:Python11117

• katholt/srst2

  Short Read Sequence Typing for Bacterial Pathogens

  Language:Python12566

• lc222/char-cnn-text-classification-tensorflow

  Character-level Convolutional Networks for Text Classification论文仿真实现

  Language:Python7238

• ShanlinKe/COVID-19

  Dissecting the Role of the Human Microbiome in COVID-19 via Metagenome-assembled Genomes

  Language:R63

• RasmussenLab/phamb

  Downstream processing of VAMB binning for Viral Elucidation

  Language:Python468

• RasmussenLab/vamb

  Variational autoencoder for metagenomic binning

  Language:Python26547

• dominicp6/ImmuneConstrainedVAE

  Dozens of vaccines protecting against SARS-CoV-2 have now been approved for public use, yet there remains a high risk that the virus evolves to escape vaccine protection. This motivates the need for a new generation of vaccines that can protect against a wider gamut of a virus’s evolutionary accessible states, not just the currently circulating strains. Computational methods such as sequence generative models can play a critical role in mapping out this state space. In particular, they can be used to screen thousands of examples of viral proteins that might pose a high risk of vaccine escape. In this work, we take steps towards such a computational method by designing and evaluating a conditional Variational Autoencoder (VAE) capable of selectively generating SARS-CoV-2 spike proteins with low immune visibility. The model is trained on $65,000$ of the most common wild-type SARS-CoV-2 sequences and uses NetMHCpan to estimate levels of exposure to human T cell immunity. The model's generated sequences are compared with those derived from two simpler generative models; a random-mutator and an 11-gram language model. We discover that although all three models are able to generate stable, structurally valid sequences, only the VAE model can generate low immunogenicity sequences sampled from a distribution that interpolates smoothly along the principal variance directions of natural sequences.

  Language:Jupyter Notebook2

• salesforce/progen

  Official release of the ProGen models

  Language:Python627117

• debbiemarkslab/EVcouplings

  Evolutionary couplings from protein and RNA sequence alignments

  Language:Jupyter Notebook24975

• lambdal/deeplearning-benchmark

  Benchmark Suite for Deep Learning

  Language:Shell25250

• tseemann/snippy

  :scissors: :zap: Rapid haploid variant calling and core genome alignment

  Language:Perl488117

• biobakery/biobakery

  bioBakery tools for meta'omic profiling

  Language:Shell26475

• asadprodhan/GPU-accelerated-guppy-basecalling

  GPU-accelerated guppy basecalling and demultiplexing on Linux

  Language:Shell173

• gencorefacility/covid19

  Variant Analysis Pipeline for COVID19

  Language:Nextflow41

• appliedmicrobiologyresearch/covgap

  Genome mapping, consensus generating, variant calling and annotation tool for SARS-COV-2

  Language:Python12

• nextstrain/nextclade_data

  Datasets for https://github.com/nextstrain/nextclade

  Language:Python3228

• hsnguyen/assembly

  Streaming assembly for MinION data

  Language:Java254

• mdcao/npScarf

  263

• neherlab/treetime

  Maximum likelihood inference of time stamped phylogenies and ancestral reconstruction

  Language:Jupyter Notebook23257

• theosanderson/chronumental

  Estimating time trees from very large phylogenies

  Language:Python256

• nextstrain/ncov

  Nextstrain build for novel coronavirus SARS-CoV-2

  Language:Python1.4k403

• PoonLab/covizu

  Rapid analysis and visualization of coronavirus genome variation

  Language:JavaScript4620

• maximilianh/multiSub

  Prepares a SARS-CoV-2 submission for GISAID, NCBI or ENA. Can read GISAID or NCBI files, or plain fasta+tsv/csv/xls. Finds files in input directory and merges everything into a single output directory. Auto-detects input file formats. Can submit the results to multiple repositories from the command line.

  Language:Python352

• cov-lineages/pangolin

  Software package for assigning SARS-CoV-2 genome sequences to global lineages.

  Language:Python430106

• epi2me-labs/wf-artic

  ARTIC SARS-CoV-2 workflow and reporting

  Language:Nextflow4935

• LPDI-EPFL/trivalent_cocktail

  Language:Roff104

• JianiC/rsv

  Nextstrain build for Human Respiratory Syncytial Virus

  Language:Python32

• salvatoreloguercio/cov2vec

  cov2vec is a systematic effort to obtain SARS CoV-2 genome embeddings by encoding viral genomes with protein language models.

  Language:Python1

• brianhie/viral-mutation

  Language modeling of viral evolution

  Language:Python13844

• happywlu/CroTrait

  A portable tool for in silico species identification, serotyping and multilocus sequence typing of Cronobacter genus

  Language:Python34