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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.

icaird-weaklysupervisedlearning

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.

multiple_instance_learning_instance_based

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

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

track

uni

Towards a general-purpose foundation model for computational pathology - Nature Medicine

uta_cancer_search

werobot

WeRoBot 是一个微信公众号开发框架

worm_sim

worm_sim developed by SLD group of Carnegie Mellon University