alxndrkalinin
ML in Comp Bio @broadinstitute. Prev PhD & postdoc in bioinfo @umich & @cuhkshenzhen.
Broad Institute of MIT and HarvardCambridge, MA
Pinned Repositories
angiodysplasia-segmentation
Wining solution and its further development for MICCAI 2017 Endoscopic Vision Challenge Angiodysplasia Detection and Localization
awesome-deepbio
A curated list of awesome deep learning applications in the field of computational biology
awesome-deepneuroimage
A curated list of awesome deep learning applications in the field of neurological image analysis
coding-interview-university
A complete computer science study plan to become a software engineer.
datasets
Images and other data from the JUMP Cell Painting Consortium
deep-review
A collaboratively written review paper on deep learning, genomics, and precision medicine
morphocell
pytorch_fnet
Three dimensional cross-modal image inference
deep-rules
Ten Quick Tips for Deep Learning in Biology
SOCRAT
A Dynamic Web Toolbox for Interactive Data Processing, Analysis, and Visualization
alxndrkalinin's Repositories
alxndrkalinin/datasets
Images and other data from the JUMP Cell Painting Consortium
alxndrkalinin/morphocell
alxndrkalinin/pytorch_fnet
Three dimensional cross-modal image inference
alxndrkalinin/alxndrkalinin.github.io
alxndrkalinin/cucim
alxndrkalinin/cytominer-eval
Common Evaluation Metrics for DataFrames
alxndrkalinin/BBDM
BBDM: Image-to-image Translation with Brownian Bridge Diffusion Models
alxndrkalinin/CellProfiler
An open-source application for biological image analysis
alxndrkalinin/copairs
Find pairs and compute metrics between them.
alxndrkalinin/cytodata.github.io
CytoData Society website
alxndrkalinin/Fluorescence-Reconstruction
alxndrkalinin/grit-benchmark
Benchmarking a metric used to evaluate a perturbation strength
alxndrkalinin/I2SB
alxndrkalinin/imagen-pytorch
Implementation of Imagen, Google's Text-to-Image Neural Network, in Pytorch
alxndrkalinin/MeshNet
MeshNet: Mesh Neural Network for 3D Shape Representation (AAAI 2019)
alxndrkalinin/Mitocheck-MAP-analysis
Utilizing the mean average precision (MAP) metric to assess reproducibility and perturbation effect on single-cell profiles in the MitoCheck dataset.
alxndrkalinin/NDC
PyTorch implementation of Neural Dual Contouring.
alxndrkalinin/PatchDDM-3D
alxndrkalinin/position-effect-correction
alxndrkalinin/pycytominer
cytominer python package
alxndrkalinin/pytorch-3dunet
3D U-Net model for volumetric semantic segmentation written in pytorch
alxndrkalinin/scib
Benchmarking analysis of data integration tools
alxndrkalinin/scikit-image
Image processing in Python
alxndrkalinin/SegLoss
A collection of loss functions for medical image segmentation
alxndrkalinin/segmentation_models_3D
Set of models for segmentation of 3D volumes
alxndrkalinin/SubdivNet
Subdivision-based Mesh Convolutional Networks.
alxndrkalinin/tutorials
CellProfiler tutorial pipelines and images
alxndrkalinin/VollSeg
Segmentation method able to detect membrane/nuclei-labelled cells with low signal-to-noise ratio and dense packing in 2D and 3D. Available via pip package vollseg.
alxndrkalinin/volumentations
Library for 3D augmentations
alxndrkalinin/voxel2mesh
Voxel2Mesh: 3D Mesh Model Generation from Volumetric Data