guopengwei's repositories
allelecounter
Counts the number of reads which map to either the reference or alternate allele at each heterozygous SNP.
bwa-hbm
Adaptation of the BWA MEM read mapper leveraging HBM on FPGAs to accelerate the SMEM algorithm
bwagpu
Burrow-Wheeler Aligner for short-read alignment (see minimap2 for long-read alignment)
cerberus
One Model is All You Need: Multi-Task Learning Enables Simultaneous Histology Image Segmentation and Classification
CONCH
A vision-language foundation model for computational pathology - Nature Medicine
DB-GPT
Revolutionizing Database Interactions with Private LLM Technology
Edge-MoE
Edge-MoE: Memory-Efficient Multi-Task Vision Transformer Architecture with Task-level Sparsity via Mixture-of-Experts
EmbeddedAI-Scope
A 3D Printed Embedded AI-based Microscope for Pathology Diagnosis
Genome-on-Diet
Genome-on-Diet is a fast and memory-frugal framework for exemplifying sparsified genomics for read mapping, containment search, and metagenomic profiling. It is much faster & more memory-efficient than minimap2 for Illumina, HiFi, and ONT reads. Described by Alser et al. (preliminary version: https://arxiv.org/abs/2211.08157).
HiPS
Histomic Prognostic Signature (HiPS): A population-level computational histologic signature for invasive breast cancer prognosis
hover_net
Simultaneous Nuclear Instance Segmentation and Classification in H&E Histology Images.
pairHMM
Gatk pairHMM use FPGA
PHMM-F1
FPGA Accelerator (Amazon F1) for the Pair-HMM Forward Algorithm of the GATK HaplotypeCaller
reetoolbox
Toolbox for measuring adversarial robustness to many transforms
SISH
Fast and scalable search of whole-slide images via self-supervised deep learning - Nature Biomedical Engineering
kmer_fpga
Demonstration of next generation sequencing accelerator
MetaFast
MetaFast is a novel metagenomic analysis tool employing efficient containment search techniques and heuristics for read mapping to achieve significant speedup while maintaining high accuracy. This positions MetaFast as an efficient solution, optimally balancing speed and precision in metagenomic analysis.
sket
This repository contains the source code for the Semantic Knowledge Extractor Tool (SKET). SKET is an unsupervised hybrid knowledge extraction system that combines a rule-based expert system with pre-trained machine learning models to extract cancer-related information from pathology reports.
SneakySnake
SneakySnake:snake: is the first and the only pre-alignment filtering algorithm that works efficiently and fast on modern CPU, FPGA, and GPU architectures. It greatly (by more than two orders of magnitude) expedites sequence alignment calculation for both short and long reads. Described in the Bioinformatics (2020) by Alser et al. https://arxiv.org/
tcga_segmentation
Whole Slide Image segmentation with weakly supervised multiple instance learning on TCGA | MICCAI2020 https://arxiv.org/abs/2004.05024
Thor
DIY 3D Printable Robotic Arm
UNI
Towards a general-purpose foundation model for computational pathology - Nature Medicine
WeRoBot
WeRoBot 是一个微信公众号开发框架