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      Target Finder of Transcription Factor (TFoTF): a novel tool to predict transcription factor‐targeted genes in cancer

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          Abstract

          Transcription factors (TFs) are key players in the regulation of gene transcription in mammalian cells. Although high‐throughput screening can be used to identify differentially expressed genes between comparable groups, the precision of the corresponding datasets is far from optimal. Here, we establish Target Finder of Transcription Factor (TFoTF), a method for the prediction of TF‐targeted genes from genomic and cancer‐related transcriptomic data. TFoTF can identify potential TF‐targeted genes in large cancer datasets and efficiently estimate correlations between TFs and their targeted genes with a significant level of specificity, sensitivity, and precision. Overall, TFoTF is an easy‐to‐use tool that can be utilized to generate testable hypotheses in the context of cancer research projects.

          Abstract

          Transcription factors (TFs) are essential for gene transcription and play an important role in tumorigenesis. To predict TF‐targeted genes, the authors developed an easy‐to‐use tool termed Target Finder of Transcription Factor (TFoTF). This de novo tool can overcome the constraint of existing prediction methods for TF‐targeted genes in cancer and can perform predictions with more specificity, sensitivity, precision, and time efficiency.

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          Most cited references25

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          Metascape provides a biologist-oriented resource for the analysis of systems-level datasets

          A critical component in the interpretation of systems-level studies is the inference of enriched biological pathways and protein complexes contained within OMICs datasets. Successful analysis requires the integration of a broad set of current biological databases and the application of a robust analytical pipeline to produce readily interpretable results. Metascape is a web-based portal designed to provide a comprehensive gene list annotation and analysis resource for experimental biologists. In terms of design features, Metascape combines functional enrichment, interactome analysis, gene annotation, and membership search to leverage over 40 independent knowledgebases within one integrated portal. Additionally, it facilitates comparative analyses of datasets across multiple independent and orthogonal experiments. Metascape provides a significantly simplified user experience through a one-click Express Analysis interface to generate interpretable outputs. Taken together, Metascape is an effective and efficient tool for experimental biologists to comprehensively analyze and interpret OMICs-based studies in the big data era.
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            clusterProfiler 4.0: A universal enrichment tool for interpreting omics data

            Summary Functional enrichment analysis is pivotal for interpreting high-throughput omics data in life science. It is crucial for this type of tool to use the latest annotation databases for as many organisms as possible. To meet these requirements, we present here an updated version of our popular Bioconductor package, clusterProfiler 4.0. This package has been enhanced considerably compared with its original version published 9 years ago. The new version provides a universal interface for functional enrichment analysis in thousands of organisms based on internally supported ontologies and pathways as well as annotation data provided by users or derived from online databases. It also extends the dplyr and ggplot2 packages to offer tidy interfaces for data operation and visualization. Other new features include gene set enrichment analysis and comparison of enrichment results from multiple gene lists. We anticipate that clusterProfiler 4.0 will be applied to a wide range of scenarios across diverse organisms.
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              ChIPseeker: an R/Bioconductor package for ChIP peak annotation, comparison and visualization.

              ChIPseeker is an R package for annotating ChIP-seq data analysis. It supports annotating ChIP peaks and provides functions to visualize ChIP peaks coverage over chromosomes and profiles of peaks binding to TSS regions. Comparison of ChIP peak profiles and annotation are also supported. Moreover, it supports evaluating significant overlap among ChIP-seq datasets. Currently, ChIPseeker contains 15 000 bed file information from GEO database. These datasets can be downloaded and compare with user's own data to explore significant overlap datasets for inferring co-regulation or transcription factor complex for further investigation.
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                Author and article information

                Contributors
                guoxiong.xu@fudan.edu.cn
                Journal
                Mol Oncol
                Mol Oncol
                10.1002/(ISSN)1878-0261
                MOL2
                Molecular Oncology
                John Wiley and Sons Inc. (Hoboken )
                1574-7891
                1878-0261
                11 February 2023
                July 2023
                : 17
                : 7 ( doiID: 10.1002/mol2.v17.7 )
                : 1246-1262
                Affiliations
                [ 1 ] Research Center for Clinical Medicine Jinshan Hospital, Fudan University Shanghai China
                [ 2 ] Department of Oncology, Shanghai Medical College Fudan University Shanghai China
                [ 3 ] Center for Tumor Diagnosis & Therapy Jinshan Hospital, Fudan University Shanghai China
                Author notes
                [*] [* ] Correspondence

                G. Xu, Research Center for Clinical Medicine, Jinshan Hospital, Fudan University, 1508 Longhang Road, Shanghai 201508, China

                Fax: +86 21 57039502

                Tel: +86 21 34189990

                E‐mail: guoxiong.xu@ 123456fudan.edu.cn

                Author information
                https://orcid.org/0000-0002-9074-8754
                Article
                MOL213388 MOLONC-22-0343.R5
                10.1002/1878-0261.13388
                10323881
                36734611
                4531f8a2-152b-4a23-9bf6-3bc31bca1b03
                © 2023 The Authors. Molecular Oncology published by John Wiley & Sons Ltd on behalf of Federation of European Biochemical Societies.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 19 January 2023
                : 04 May 2022
                : 02 February 2023
                Page count
                Figures: 12, Tables: 0, Pages: 1262, Words: 8344
                Funding
                Funded by: National Natural Science Foundation of China , doi 10.13039/501100001809;
                Award ID: 81872121
                Funded by: Science and Technology Commission of Shanghai Municipality , doi 10.13039/501100003399;
                Award ID: 17ZR1404100
                Categories
                Cancer and Oncology
                Transcriptomics
                Research Article
                Research Articles
                Custom metadata
                2.0
                July 2023
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.3.1 mode:remove_FC converted:06.07.2023

                Oncology & Radiotherapy
                gene expression,position weight matrices,stat1,transcriptional regulation,tumorigenesis

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