j-atika

j-atika's Stars

• j-atika/RCC-MDSC-SpatialDist-Model

  Deep-learning model development for spatial transcriptomics analysis in RCC tumor microenvironment. Read the README.md for more details. #AI #ComputationalOncology #RCC #MDSC #SpatialDistribution #AIModel #ComputationalBiology

  1

• junqiangchen/KiPA2022-Challenge

  KiPA2022——Multi-Structure Segment for Renal Cancer Treatment.

  Language:Python62

• francismjenkins/Capstone_project

  Differential gene expression analysis of TCGA dataset containing expression data for normal and kidney cancer cells

  Language:Jupyter Notebook62

• SVAI/KidneyBean

  Drug-gene interaction database scraper for rare kidney cancer treatment research proposals

  Language:Jupyter Notebook23

• khuhm/deep-kidney-cancer

  Deep Learning for End-to-End Kidney Cancer Diagnosis on Multi-Phase Abdominal Computed Tomography

  Language:Python15

• heavywatal/tumopp

  🦀 Tumor growth simulation in C++/R

  Language:C++192

• getzlab/deTiN

  DeTiN is designed to measure tumor-in-normal contamination and improve somatic variant detection sensitivity when using a contaminated matched control.

  Language:Jupyter Notebook4921

• digitalcytometry/ecotyper

  EcoTyper is a machine learning framework for large-scale identification of cell states and cellular ecosystems from gene expression data.

  Language:R18442

• ebi-ait/hca-ebi-wrangler-central

  This repo is for tracking work related to wrangling datasets for the HCA, associated tasks and for maintaining related documentation.

  Language:Jupyter Notebook72

• cit-bioinfo/WISP

  Weighted In Silico Pathology: a novel approach to assess intra-tumoral heterogeneity

  Language:R4

• rahmanidashti/PPINetworkAnalysis

  Comparison of Tumor and Normal Cells Protein-Protein Interaction Network Parameters

  Language:R4

• broadinstitute/celligner

  tumor - cancer cell line alignment. Use it on the depmap portal or install it with pip.

  Language:Jupyter Notebook74

• tharunchitipolu/Breast-cancer-prediction-using-machine-learning

  predict whether the tumor is Malignant or Benign.

  Language:Jupyter Notebook61

• rmsandu/segmentation-eval

  Extract and evaluate radiomics for liver cancer tumors from DICOM segmentation masks. Using SimpleITK, PyRadiomics and PyDicom.

  Language:Python234

• dellytools/delly

  DELLY2: Structural variant discovery by integrated paired-end and split-read analysis

  Language:C++441137

• sigven/pcgr

  Personal Cancer Genome Reporter (PCGR)

  Language:R25448

• guillaumefrd/brain-tumor-mri-dataset

  Utilities to download and load an MRI brain tumor dataset with Python, providing 2D slices, tumor masks and tumor classes.

  Language:Jupyter Notebook9529

• merry75/educative.io_courses

  this is downloadings of all educative.io free student subscription courses as pdf from GitHub student pack

  3.1k