Discover our collection of 9 research tools and applications for machine learning.
Found 9 of 9 tools
Kover is an out-of-core implementation of rule-based machine learning algorithms that has been tailored for genomic biomarker discovery. It produces highly interpretable models, based on k-mers, that explicitly highlight genotype-to-phenotype associations.
A supervised learning framework for chromatin loop detection in genome-wide contact maps. It can be used to visualize Hi-C, ChIA-PET, HiCHiP, PLAC-Seq, Capture Hi-C data.
AlphaFold is an AI system developed by Google DeepMind that predicts protein 3D structures from amino acid sequences, achieving accuracy comparable to experimental methods. It is accessible through the European Bioinformatics Institute (EBI) and a GitHub repository.
Sequential regulatory activity predictions with deep convolutional neural networks.
CCS: Generate Highly Accurate Single-Molecule Consensus Reads (HiFi Reads)
CellTypist is an automated cell type annotation tool for scRNA-seq datasets on the basis of logistic regression classifiers optimised by the stochastic gradient descent algorithm. CellTypist allows for cell prediction using either built-in (with a current focus on immune sub-populations) or custom models, in order to assist in the accurate classification of different cell types and subtypes.
A deep learning genome-mining strategy for biosynthetic gene cluster prediction | BGC Detection and Classification Using Deep Learning | DeepBGC: Biosynthetic Gene Cluster detection and classification | DeepBGC detects BGCs in bacterial and fungal genomes using deep learning. DeepBGC employs a Bidirectional Long Short-Term Memory Recurrent Neural Network and a word2vec-like vector embedding of Pfam protein domains. Product class and activity of detected BGCs is predicted using a Random Forest classifier
Tool for interactive bioimage classification, segmentation and analysis.
llama.cpp is an open-source C/C++ inference engine for running large language models (LLMs) locally on consumer hardware, supporting CPU and GPU execution with optimized performance and minimal dependencies.