Multi gene mutation signatures in colorectal cancer patients: Predict for the diagnosis, pathological classification, staging and prognosis

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Multi gene mutation signatures in colorectal cancer patients: Predict for the diagnosis, pathological classification, staging and prognosis

Kim Khánh 58 16 pdf

Identifying gene mutation signatures will enable a better understanding for the occurrence and development of colorectal cancer (CRC), and provide some potential biomarkers for clinical practice. |

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Multi gene mutation signatures in colorectal cancer patients: Predict for the diagnosis, pathological classification, staging and prognosis

Identifying gene mutation signatures will enable a better understanding for the occurrence and development of colorectal cancer (CRC), and provide some potential biomarkers for clinical practice. |

A comparative study of survival models for breast cancer prognostication revisited: The benefits of multi-gene models

GO2MSIG, an automated GO based multi-species gene set generator for gene set enrichment analysis

PROMO: An interactive tool for analyzing clinically-labeled multi-omic cancer datasets

Predicting multi-level drug response with gene expression profile in multiple myeloma using hierarchical ordinal regression

CGINet: Graph convolutional network‑based model for identifying chemical‑gene interaction in an integrated multi‑relational graph

Kerfuffle: A web tool for multi-species gene colocalization analysis

CoMAGC: A corpus with multi-faceted annotations of gene-cancer relations

Detection of class 1 integron-associated gene cassettes of multi-drug resistant Salmonella strains isolated from food at conventional markets in Ho Chi Minh city

Unsupervised gene selection using biological knowledge: Application in sample clustering

RapidGSEA: Speeding up gene set enrichment analysis on multi-core CPUs and CUDA-enabled GPUs

Đang chuẩn bị liên kết để tải về tài liệu: Multi gene mutation signatures in colorectal cancer patients: Predict for the diagnosis, pathological classification, staging and prognosis

Identifying gene mutation signatures will enable a better understanding for the occurrence and development of colorectal cancer (CRC), and provide some potential biomarkers for clinical practice. |

A comparative study of survival models for breast cancer prognostication revisited: The benefits of multi-gene models

GO2MSIG, an automated GO based multi-species gene set generator for gene set enrichment analysis

PROMO: An interactive tool for analyzing clinically-labeled multi-omic cancer datasets

Predicting multi-level drug response with gene expression profile in multiple myeloma using hierarchical ordinal regression

CGINet: Graph convolutional network‑based model for identifying chemical‑gene interaction in an integrated multi‑relational graph

Kerfuffle: A web tool for multi-species gene colocalization analysis

CoMAGC: A corpus with multi-faceted annotations of gene-cancer relations

Detection of class 1 integron-associated gene cassettes of multi-drug resistant Salmonella strains isolated from food at conventional markets in Ho Chi Minh city

Unsupervised gene selection using biological knowledge: Application in sample clustering

RapidGSEA: Speeding up gene set enrichment analysis on multi-core CPUs and CUDA-enabled GPUs

Đang chuẩn bị liên kết để tải về tài liệu:
Multi gene mutation signatures in colorectal cancer patients: Predict for the diagnosis, pathological classification, staging and prognosis