Predicting potential drug-drug interactions by integrating chemical, biological, phenotypic and network data

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Predicting potential drug-drug interactions by integrating chemical, biological, phenotypic and network data

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Drug-drug interactions (DDIs) are one of the major concerns in drug discovery. Accurate prediction of potential DDIs can help to reduce unexpected interactions in the entire lifecycle of drugs, and are important for the drug safety surveillance. |

Đang chuẩn bị liên kết để tải về tài liệu:
Predicting potential drug-drug interactions by integrating chemical, biological, phenotypic and network data

Drug-drug interactions (DDIs) are one of the major concerns in drug discovery. Accurate prediction of potential DDIs can help to reduce unexpected interactions in the entire lifecycle of drugs, and are important for the drug safety surveillance. |

Báo cáo lâm nghiệp: "Predicting the potential distribution of Sirex noctilio (Hymenoptera: Siricidae), a significant exotic pest of Pinus plantations"

Báo cáo y học: " The potential role of appetite in predicting weight changes during treatment with olanzapine"

CREB3L1 as a potential biomarker predicting response of triple negative breast cancer to doxorubicin-based chemotherapy

A novel computational model for predicting potential LncRNA‑disease associations based on both direct and indirect features of LncRNA‑disease pairs

Comprehensive analyses of competing endogenous RNA networks reveal potential biomarkers for predicting hepatocellular carcinoma recurrence

The platelet to lymphocyte ratio is a potential inflammatory marker predicting the effects of adjuvant chemotherapy in patients with stage II colorectal cancer

Benchmark of computational methods for predicting microRNA-disease associations

N6-methyladenosine-related lncRNAs identified as potential biomarkers for predicting the overall survival of Asian gastric cancer patients

N6-Methyladenosine-Related lncRNAs as potential biomarkers for predicting prognoses and immune responses in patients with cervical cancer

Predicting the potential distribution area of Solidago niederederi (Asteraceae)

Đang chuẩn bị liên kết để tải về tài liệu: Predicting potential drug-drug interactions by integrating chemical, biological, phenotypic and network data

Drug-drug interactions (DDIs) are one of the major concerns in drug discovery. Accurate prediction of potential DDIs can help to reduce unexpected interactions in the entire lifecycle of drugs, and are important for the drug safety surveillance. |

Báo cáo lâm nghiệp: "Predicting the potential distribution of Sirex noctilio (Hymenoptera: Siricidae), a significant exotic pest of Pinus plantations"

Báo cáo y học: " The potential role of appetite in predicting weight changes during treatment with olanzapine"

CREB3L1 as a potential biomarker predicting response of triple negative breast cancer to doxorubicin-based chemotherapy

A novel computational model for predicting potential LncRNA‑disease associations based on both direct and indirect features of LncRNA‑disease pairs

Comprehensive analyses of competing endogenous RNA networks reveal potential biomarkers for predicting hepatocellular carcinoma recurrence

The platelet to lymphocyte ratio is a potential inflammatory marker predicting the effects of adjuvant chemotherapy in patients with stage II colorectal cancer

Benchmark of computational methods for predicting microRNA-disease associations

N6-methyladenosine-related lncRNAs identified as potential biomarkers for predicting the overall survival of Asian gastric cancer patients

N6-Methyladenosine-Related lncRNAs as potential biomarkers for predicting prognoses and immune responses in patients with cervical cancer

Predicting the potential distribution area of Solidago niederederi (Asteraceae)

Đang chuẩn bị liên kết để tải về tài liệu:
Predicting potential drug-drug interactions by integrating chemical, biological, phenotypic and network data