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awesome-deep-learning

A curated list of awesome Deep Learning tutorials, projects and communities.

bioc2018

BioC 2018: Where Software and Biology Connect

concurrenttherapysecondcancer

A biologically motivated mathematical formalism is used to estimate the relative risks of breast, lung and thyroid cancers in childhood cancer survivors due to concurrent therapy regimen. This model specifically includes possible organ-specific interaction between radiotherapy and chemotherapy. The model predicts relative risks for developing secondary cancers after chemotherapy in breast, lung and thyroid tissues, and compared with the epidemiological data.

coregx

Shared code for both PharmacoGx and RadioGx

crosstalknet

A web resource to analyze bi-partite and non-bipartite biological networks.

drugstroma

epistromaimmune

histolab

Library for Digital Pathology Image Processing

immune_deconvolution_benchmark

Reproducible pipeline for "Comprehensive evaluation of cell-type quantification methods for immuno-oncology", Sturm et al. 2019, https://doi.org/10.1093/bioinformatics/btz363

liger

R package for integrating and analyzing multiple single-cell datasets

metagxdata

Analysis pipeline for the MetaGxData package compedium (version 2.3)

mutationalpatterns

R package for extracting and visualizing mutational patterns in base substitution catalogues

protontherapy-tcp-relapse-secondcancer

We incorporated tumour relapse kinetics into the TCP framework and calculate the associated second cancer risks. To calculate proton therapy-induced secondary cancer induction, we used the well-known biologically motivated mathematical model, initiation–inactivation–proliferation formalism. We used the available in vitro data for the linear energy transfer (LET) dependence of cell killing and mutation induction parameters.

pvactools

radiationgenesigdb

A comprehensive database of oxic and hypoxic radiation response gene expression signatures

radiogenomicsscript

radiogx

RadioGx and PharmacoGx: Integrated prediction tools for combining radiotherapy with systemic agents

radiogx-analysis

sequentialtherapysecondcancer

We employed a biologically motivated mathematical model to estimate the radiation and chemotherapy-induced relative risks of thyroid malignancies in four childhood cancer study survivors (CCSS) data sets. the predictions of radiation and chemotherapy-induced relative risks of secondary thyroid malignancies using the mathematical model are compared against four clinical datasets from the CCSS cohort. Moreover, the extracted average value of growth rate of premalignant cells is 0.8175 (per day) and the extracted chemo-induced mutation rate is of the order of 10(−10) (per unit of chemotherapeutic dose).

spatial-evolutionary-modeling--matlabcode