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16 papers found.
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Does ALK-rearrangement predict favorable response to the therapy of bevacizumab plus pemetrexed in advanced non-small-cell lung cancer? Case report and literature review

Background Advanced ALK-rearranged non-small cell lung cancer (NSCLC) patients will develop acquired resistance after anaplastic lymphoma kinase (ALK) inhibitors therapies. Vascular endothelial growth factor-A (VEGF-A) production and tumor vessel formation were found to be more significantly enriched in ALK-rearrangement NSCLC than that in epidermal growth factor receptor or ...

Application of dynamic topic models to toxicogenomics data

Background All biological processes are inherently dynamic. Biological systems evolve transiently or sustainably according to sequential time points after perturbation by environment insults, drugs and chemicals. Investigating the temporal behavior of molecular events has been an important subject to understand the underlying mechanisms governing the biological system in response ...

A novel procedure on next generation sequencing data analysis using text mining algorithm

Background Next-generation sequencing (NGS) technologies have provided researchers with vast possibilities in various biological and biomedical research areas. Efficient data mining strategies are in high demand for large scale comparative and evolutional studies to be performed on the large amounts of data derived from NGS projects. Topic modeling is an active research field in ...

Deciphering miRNA transcription factor feed-forward loops to identify drug repurposing candidates for cystic fibrosis

Background Cystic fibrosis (CF) is a fatal genetic disorder caused by mutations in the CF transmembrane conductance regulator (CFTR) gene that primarily affects the lungs and the digestive system, and the current drug treatment is mainly able to alleviate symptoms. To improve disease management for CF, we considered the repurposing of approved drugs and hypothesized that specific ...

A heuristic approach to determine an appropriate number of topics in topic modeling

Background Topic modelling is an active research field in machine learning. While mainly used to build models from unstructured textual data, it offers an effective means of data mining where samples represent documents, and different biological endpoints or omics data represent words. Latent Dirichlet Allocation (LDA) is the most commonly used topic modelling method across a wide ...

Of text and gene – using text mining methods to uncover hidden knowledge in toxicogenomics

Mikyung Lee 0 Zhichao Liu 0 Reagan Kelly Weida Tong 0 Equal contributors Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, U.S. Food and Drug Administration

Anti-Metastasis Effect of Fucoidan from Undaria pinnatifida Sporophylls in Mouse Hepatocarcinoma Hca-F Cells

Metastasis is one of the major causes of cancer-related death. It is a complex biological process involving multiple genes, steps, and phases. It is also closely connected to many biological activities of cancer cells, such as growth, invasion, adhesion, hematogenous metastasis, and lymphatic metastasis. Fucoidan derived from Undaria pinnatifida sporophylls (Ups-fucoidan) is a ...

A phenome-guided drug repositioning through a latent variable model

Background The phenome represents a distinct set of information in the human population. It has been explored particularly in its relationship with the genome to identify correlations for diseases. The phenome has been also explored for drug repositioning with efforts focusing on the search space for the most similar candidate drugs. For a comprehensive analysis of the phenome, we ...

Mining FDA drug labels using an unsupervised learning technique - topic modeling

Background The Food and Drug Administration (FDA) approved drug labels contain a broad array of information, ranging from adverse drug reactions (ADRs) to drug efficacy, risk-benefit consideration, and more. However, the labeling language used to describe these information is free text often containing ambiguous semantic descriptions, which poses a great challenge in retrieving ...

Investigating drug repositioning opportunities in FDA drug labels through topic modeling

Background Drug repositioning offers an opportunity to revitalize the slowing drug discovery pipeline by finding new uses for currently existing drugs. Our hypothesis is that drugs sharing similar side effect profiles are likely to be effective for the same disease, and thus repositioning opportunities can be identified by finding drug pairs with similar side effects documented in ...

In situ U-Pb dating of titanite by LA-ICPMS

Titanite is an ideal mineral for U-Pb isotopic dating because of its relatively high U, Th and Pb contents. Here, we developed a technique for U-Pb dating of titanite using the 193 nm ArF laser-ablation system and Agilent 7500a Q-ICP-MS. Standards of titanite (BLR-1 and OLT-1) and zircon (91500 and GJ-1) were dated using single spot and line raster scan analytical methods. To check ...

Translating Clinical Findings into Knowledge in Drug Safety Evaluation - Drug Induced Liver Injury Prediction System (DILIps)

Drug-induced liver injury (DILI) is a significant concern in drug development due to the poor concordance between preclinical and clinical findings of liver toxicity. We hypothesized that the DILI types (hepatotoxic side effects) seen in the clinic can be translated into the development of predictive in silico models for use in the drug discovery phase. We identified 13 hepatotoxic ...

In situ U-Pb dating of xenotime by laser ablation (LA)-ICP-MS

Xenotime is an ideal mineral for U-Th-Pb isotopic dating because of its relatively high U and Th contents, but typically low concentration of common Pb. These characteristics, and the fact that it is widespread throughout various types of rocks, suggest that the U-Th-Pb dating of xenotime has broad applications. Studies of U-Pb dating on xenotime by ion microprobe (such as SHRIMP) ...

Constructing a robust protein-protein interaction network by integrating multiple public databases

Background Protein-protein interactions (PPIs) are a critical component for many underlying biological processes. A PPI network can provide insight into the mechanisms of these processes, as well as the relationships among different proteins and toxicants that are potentially involved in the processes. There are many PPI databases publicly available, each with a specific focus. The ...

atBioNet– an integrated network analysis tool for genomics and biomarker discovery

BackgroundLarge amounts of mammalian protein-protein interaction (PPI) data have been generated and are available for public use. From a systems biology perspective, Proteins/genes interactions encode the key mechanisms distinguishing disease and health, and such mechanisms can be uncovered through network analysis. An effective network analysis tool should integrate different ...