標(biāo)題: Titlebook: Cancer Bioinformatics; Alexander Krasnitz Book 2019 Springer Science+Business Media, LLC, part of Springer Nature 2019 cancer informatics. [打印本頁] 作者: Limbic-System 時(shí)間: 2025-3-21 19:29
書目名稱Cancer Bioinformatics影響因子(影響力)
作者: Essential 時(shí)間: 2025-3-22 00:03
CORE: A Software Tool for Delineating Regions of Recurrent DNA Copy Number Alteration in Cancer,ften represent regions with altered DNA copy number, and their collections exhibit recurrent features, characteristic of a given cancer type. Cores of Recurrent Events (CORE) is a versatile computational tool for identification of such recurrent features. Here we provide practical guidance for the use of CORE, implemented as an eponymous R package.作者: BLUSH 時(shí)間: 2025-3-22 00:25
1064-3745 ed, explanations of the input and output formats, and illustrative examples of applications...Authoritative and cutting-edge,?.Cancer Bioinformatics: Methods and Protocols.?aims to support researchers performing computational analysis of cancer-related data..978-1-4939-9404-5978-1-4939-8868-6Series ISSN 1064-3745 Series E-ISSN 1940-6029 作者: LEERY 時(shí)間: 2025-3-22 04:54 作者: 值得尊敬 時(shí)間: 2025-3-22 09:26 作者: 槍支 時(shí)間: 2025-3-22 14:05 作者: 槍支 時(shí)間: 2025-3-22 17:35
In Silico Oncology Drug Repositioning and Polypharmacology,tocols are appropriate for target-centric drug repositioning to various complex diseases, but expertise is still necessary to perform the specific oncology projects based on the cancer targets of interest.作者: BUDGE 時(shí)間: 2025-3-22 23:42 作者: Extricate 時(shí)間: 2025-3-23 03:54 作者: 一小塊 時(shí)間: 2025-3-23 09:06
Heinz B?ker,Peter Hartwich,Georg Northoffhe best-suited mathematical function to describe tumor growth for experimental xenograft mouse tumor models and how to parametrize them. Common pitfalls and problems are described as well as methods to avoid them.作者: Climate 時(shí)間: 2025-3-23 10:16 作者: nostrum 時(shí)間: 2025-3-23 14:38 作者: 施舍 時(shí)間: 2025-3-23 18:13
Book 2019o attract a broad readership, ranging from active researchers in computational biology and bioinformatics developers, clinical oncologists, and anti-cancer drug developers wishing to rationalize their search for new compounds. Written in the highly successful?.Methods in Molecular Biology.?series fo作者: –DOX 時(shí)間: 2025-3-24 00:49
Hallucinations in Parkinson’s Disease of the problem of computational genomic SV detection using next-generation sequencing (NGS) platforms, along with a brief overview of typical approaches for addressing this problem. It also discusses the general protocol that should be followed to analyze a cancer genome for SV detection in NGS data.作者: 或者發(fā)神韻 時(shí)間: 2025-3-24 05:46 作者: menopause 時(shí)間: 2025-3-24 08:32 作者: 博愛家 時(shí)間: 2025-3-24 12:29
https://doi.org/10.1007/978-3-658-34174-9ghts following the study of the mechanisms underlying the differential expression of these lncRNAs in association with and possibly contributing to cancer recurrence. Ultimately, the expanding knowledge of the function of lncRNAs curated by computational analysis will suggest new targets for cancer treatment.作者: ALE 時(shí)間: 2025-3-24 15:59
Neuropsychoanalytical Research,d describe the computational steps and statistical considerations going from processing of the raw array data to analysis of differential methylation. Moreover, we provide detailed guidelines on how to perform tumor subtype classification based on DNA methylation signatures.作者: Nebulous 時(shí)間: 2025-3-24 22:19
1064-3745 tion advice from the experts.This volume covers a wide variety of state of the art cancer-related methods and tools for data analysis and interpretation. Chapters were designed to attract a broad readership, ranging from active researchers in computational biology and bioinformatics developers, clin作者: 祖先 時(shí)間: 2025-3-25 03:07
Neuropsychoanalytische Forschung,his chapter, we describe a fast and reliable analysis pipeline to study allele-specific expression in cancer using next-generation sequencing data. The pipeline provides a gene-level analysis approach that exploits paired germline DNA and tumor RNA sequencing data and benefits from parallel computation resources when available.作者: NOT 時(shí)間: 2025-3-25 05:07 作者: Dealing 時(shí)間: 2025-3-25 10:55 作者: 堅(jiān)毅 時(shí)間: 2025-3-25 14:40
Somatization and Bodily Distress DisorderT), and its eponymous R language implementation. TBEST employs hierarchical clustering to partition the data at a user-specified level of significance. Functionalities of the package are illustrated using as an example a benchmark data set of mRNA expression levels in leukemia.作者: 過于光澤 時(shí)間: 2025-3-25 17:13 作者: 不真 時(shí)間: 2025-3-25 21:49 作者: 羞辱 時(shí)間: 2025-3-26 03:53 作者: HATCH 時(shí)間: 2025-3-26 05:25 作者: 正論 時(shí)間: 2025-3-26 10:15 作者: 斷言 時(shí)間: 2025-3-26 14:23
Predictive Modeling of Anti-Cancer Drug Sensitivity from Genetic Characterizations,to arrive at an integrated predictive model. Integrated modeling employs the complementary information from heterogeneous genetic characterizations to improve the prediction error as well as lowering the error confidence interval.作者: 不愿 時(shí)間: 2025-3-26 16:50 作者: AMITY 時(shí)間: 2025-3-26 23:19
Identification of Mutated Cancer Driver Genes in Unpaired RNA-Seq Samples,nvolves thorough data cleaning and extensive annotation, which enable the selection for somatic mutations with functional impact and the prioritization of genes relevant to the carcinogenic processes in the input samples.作者: braggadocio 時(shí)間: 2025-3-27 01:32
A Computational Protocol for Detecting Somatic Mutations by Integrating DNA and RNA Sequencing, sequencing. The computational protocol described here enables an investigator to detect somatic mutations through integrating DNA and RNA sequencing from patient-matched tumor DNA, tumor RNA, and germline specimens via the open source software, 作者: conduct 時(shí)間: 2025-3-27 07:28
Computational Analysis of lncRNA Function in Cancer,ghts following the study of the mechanisms underlying the differential expression of these lncRNAs in association with and possibly contributing to cancer recurrence. Ultimately, the expanding knowledge of the function of lncRNAs curated by computational analysis will suggest new targets for cancer treatment.作者: 鞠躬 時(shí)間: 2025-3-27 12:21
Computational and Statistical Analysis of Array-Based DNA Methylation Data,d describe the computational steps and statistical considerations going from processing of the raw array data to analysis of differential methylation. Moreover, we provide detailed guidelines on how to perform tumor subtype classification based on DNA methylation signatures.作者: 值得 時(shí)間: 2025-3-27 16:25 作者: MEN 時(shí)間: 2025-3-27 18:22
Building Portable and Reproducible Cancer Informatics Workflows: An RNA Sequencing Case Study,gm of co-locating massive datasets with the computational resources to analyze them. The CGC was designed to allow researchers to easily find the data they need and analyze it with robust applications in a scalable and reproducible fashion. To enable this, individual tools are packaged within Docker作者: 混亂生活 時(shí)間: 2025-3-28 00:11 作者: 興奮過度 時(shí)間: 2025-3-28 02:15 作者: Offbeat 時(shí)間: 2025-3-28 09:26 作者: 下邊深陷 時(shí)間: 2025-3-28 13:03 作者: Ossification 時(shí)間: 2025-3-28 15:09 作者: monopoly 時(shí)間: 2025-3-28 21:57 作者: GULLY 時(shí)間: 2025-3-29 00:10
Computational Methods for Identification of T Cell Neoepitopes in Tumors,ethods have enabled discovery of tumor-specific mutations leading to protective T cell neoepitopes. Many of the successes are enabled by computational methods, which facilitate processing of raw data, mapping of mutations, and prediction of neoepitopes. In this book chapter, we provide an overview o作者: 提升 時(shí)間: 2025-3-29 03:21 作者: CHARM 時(shí)間: 2025-3-29 09:37
Computational Methods for Subtyping of Tumors and Their Applications for Deciphering Tumor Heterogemethylation, and gene expression) for a large number of tumors. This activity has provided unique opportunities and challenges to stratify tumors and decipher tumor heterogeneity. In this chapter, we summarize several computational methods to address the challenge of tumor stratification with differ作者: 臥虎藏龍 時(shí)間: 2025-3-29 14:20
Statistically Supported Identification of Tumor Subtypes,ide practical guidance to the use of a recently developed statistical subtyping tool, termed Tree Branches Evaluated Statistically for Tightness (TBEST), and its eponymous R language implementation. TBEST employs hierarchical clustering to partition the data at a user-specified level of significance作者: 一再困擾 時(shí)間: 2025-3-29 19:11 作者: 牢騷 時(shí)間: 2025-3-29 22:42 作者: 進(jìn)步 時(shí)間: 2025-3-30 01:03 作者: 豎琴 時(shí)間: 2025-3-30 06:02 作者: 密切關(guān)系 時(shí)間: 2025-3-30 12:09
Methods in Molecular Biologyhttp://image.papertrans.cn/c/image/221043.jpg作者: 某人 時(shí)間: 2025-3-30 13:32
Cancer Bioinformatics978-1-4939-8868-6Series ISSN 1064-3745 Series E-ISSN 1940-6029 作者: 離開真充足 時(shí)間: 2025-3-30 16:37
Posterior Cortical Atrophy (PCA)arge volumes of data from their experiments. Those responsible for production of this data often analyze a narrow subset of this data based on the research question they are trying to address: this is the case whether or not they are acting independently or in conjunction with a large-scale cancer g作者: BLUSH 時(shí)間: 2025-3-30 22:43
The Possible Talents of Tourette Syndromegm of co-locating massive datasets with the computational resources to analyze them. The CGC was designed to allow researchers to easily find the data they need and analyze it with robust applications in a scalable and reproducible fashion. To enable this, individual tools are packaged within Docker作者: hysterectomy 時(shí)間: 2025-3-31 04:42
Hallucinations in Parkinson’s Diseaseariants (SV) are one class of abnormalities that can lead to cancer onset by, for example, deactivating tumor suppressor genes and by upregulating oncogenes. Detecting and classifying these variants?can lead to improved therapies and diagnostics for cancer patients..This chapter provides an overview作者: 不舒服 時(shí)間: 2025-3-31 08:34 作者: anachronistic 時(shí)間: 2025-3-31 11:29 作者: Exposition 時(shí)間: 2025-3-31 16:19 作者: guzzle 時(shí)間: 2025-3-31 18:43
