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3y

3y原创技术文章导航

ailearning

AiLearning: 机器学习 - MachineLearning - ML、深度学习 - DeepLearning - DL、自然语言处理 NLP

augustus

Genome annotation with AUGUSTUS

awesome-architecture

架构师技术图谱，助你早日成为架构师

awesome-roadmaps

Awesome RoadMaps for Coder, Programming Language, Software Engineering, Web, Backend, Distributed Infrastructure, DataScience & AI | 程序员的进阶之路

awesome-single-cell

Community-curated list of software packages and data resources for single-cell, including RNA-seq, ATAC-seq, etc.

beautiful-visualization-with-r

《R语言数据可视化之美》配套代码

blog

write something.

book

braker

BRAKER is a pipeline for fully automated prediction of protein coding gene structures with GeneMark-ES/ET and AUGUSTUS in novel eukaryotic genomes

deeplearning-500-questions

深度学习500问，以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述，以帮助自己及有需要的读者。 全书分为18个章节，50余万字。由于水平有限，书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作，联系[email protected] 版权所有，违权必究 Tan 2018.06

django

The Web framework for perfectionists with deadlines.

doubi-ssr

drop-seq

Java tools for analyzing Drop-seq data

dropbead

dropseqrunner

Pipeline for processing single-cell RNA-seq data (drop-seq)

getawaybsg

逃离北上广

gofeat

GO FEAT: a rapid web-based functional annotation tool for genomic and transcriptomic data

guideseq

Analysis pipeline for the GUIDE-seq assay. For news, see:

harmony

Fast, sensitive and accurate integration of single-cell data with Harmony

hello

learn to establish a repository.

hexsticker

:sparkles: Hexagon sticker in R

java-learn

Java learn

jmzeng1314-5years-summarize

leetcode-go

✅ Solutions to LeetCode by Go, 100% test coverage, runtime beats 100% / LeetCode 题解

machine-learning-notes

My continuously updated Machine Learning, Probabilistic Models and Deep Learning notes and demos (2000+ slides) 我不间断更新的机器学习，概率模型和深度学习的讲义(2000+页)和视频链接

mnweeklycategory

码农周刊一周精选分类

mosaicforecast

A mosaic detecting software based on phasing and random forest

ngs-pipeline

By study this, it won't be costly or time-consuming to customize a NGS data analysis pipeline

ntu-hsuantienlin-machinelearning