Software

Research software and computational tools developed by MIDAS Lab.

Selected projects

Selected software and computational resources developed by MIDAS Lab.

Research Code

PRIME

A probabilistic imputation method for reducing dropout effects in single-cell RNA sequencing data.

PRIME: a probabilistic imputation method to reduce dropout effects in single-cell RNA sequencing

Bioinformatics, 2020

Benchmark / Resource

NAPAbench 2

A benchmark and network synthesis resource for generating realistic protein-protein interaction network families and evaluating network alignment algorithms.

NAPAbench 2: A network synthesis algorithm for generating realistic protein-protein interaction (PPI) network families

PLOS ONE, 2020

Research Code

CUFID-align

A network alignment method that estimates protein correspondence using steady-state network flow over integrated protein-protein interaction networks.

Effective comparative analysis of protein-protein interaction networks by measuring the steady-state network flow using a Markov model

BMC Bioinformatics, 2016

Research outputs

All Software

11 projects

Browse software, source code, web applications, pipelines, and computational resources.

Web Application

PixelCut

Active

A zero-configuration tool that uses computer vision to predict 3′-end trimming positions from FastQC quality reports for 16S rRNA sequencing.

PixelCut: A Unified Solution for Zero-Configuration 16S rRNA Trimming via Computer Vision

Current Issues in Molecular Biology, 2025

Web Application

REDalign

Active

A deep-learning method and web application for accurate RNA structural alignment using a residual encoder-decoder network.

REDalign: accurate RNA structural alignment using residual encoder-decoder network

BMC Bioinformatics, 2024

Research Code

GRACE

Maintained

A graph-autoencoder-based method for single-cell clustering through ensemble cell-to-cell similarity learning.

GRACE: Graph autoencoder based single-cell clustering through ensemble similarity learning

PLOS ONE, 2023

Web Application

LSTM4piRNA

Active

A deep-learning web application based on long short-term memory networks for efficient piRNA detection in large-scale genome databases.

LSTM4piRNA: Efficient piRNA Detection in Large-Scale Genome Databases Using a Deep Learning-Based LSTM Network

International Journal of Molecular Sciences, 2023

Research Code

SICLEN

Maintained

A single-cell clustering method that constructs an ensemble cell-to-cell similarity network for robust cluster identification.

Accurate Single-Cell Clustering through Ensemble Similarity Learning

Genes, 2021

Research Code

PRIME

Maintained

A probabilistic imputation method for reducing dropout effects in single-cell RNA sequencing data.

PRIME: a probabilistic imputation method to reduce dropout effects in single-cell RNA sequencing

Bioinformatics, 2020

Benchmark / Resource

NAPAbench 2

Maintained

A benchmark and network synthesis resource for generating realistic protein-protein interaction network families and evaluating network alignment algorithms.

NAPAbench 2: A network synthesis algorithm for generating realistic protein-protein interaction (PPI) network families

PLOS ONE, 2020

Research Code

scCLUE

Maintained

An ensemble feature-selection and similarity-learning method for robust clustering of single-cell RNA sequencing data.

Effective single-cell clustering through ensemble feature selection and similarity measurements

Computational Biology and Chemistry, 2020

Research Code

ClusterM

Legacy

A scalable algorithm for predicting conserved protein complexes across multiple protein-protein interaction networks.

ClusterM: a scalable algorithm for computational prediction of conserved protein complexes across multiple protein interaction networks

BMC Genomics, 2020

Research Code

TOPAS

Maintained

A network-based algorithm for fast and accurate structural alignment of RNA sequences using sequence and predicted secondary-structure information.

TOPAS: network-based structural alignment of RNA sequences

Bioinformatics, 2019

Research Code

CUFID-align

Maintained

A network alignment method that estimates protein correspondence using steady-state network flow over integrated protein-protein interaction networks.

Effective comparative analysis of protein-protein interaction networks by measuring the steady-state network flow using a Markov model

BMC Bioinformatics, 2016