iPGDAC, An Integrative Proteogenomic Data Analysis Center for CPTAC
iPGDAC,CPTAC 综合蛋白质组数据分析中心
基本信息
- 批准号:10632121
- 负责人:
- 金额:$ 86.41万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2022
- 资助国家:美国
- 起止时间:2022-06-01 至 2027-05-31
- 项目状态:未结题
- 来源:
- 关键词:AccelerationAddressAmino Acid SequenceAreaBase SequenceBenchmarkingBiologicalBiological AssayBiological MarkersBiological ModelsCancer BiologyCenter for Translational Science ActivitiesClinicalClinical DataClinical TrialsCollaborationsCommunitiesDataData AnalysesData SetDiseaseFundingGenomicsGoalsHumanImmunophenotypingIndividualKnowledgeLeadershipMalignant NeoplasmsMass Spectrum AnalysisMolecularNetwork-basedPathway AnalysisPathway interactionsPatientsPeptidesPhasePhenotypePlayPortraitsPost-Translational Modification SitePost-Translational Protein ProcessingPrognosisProteinsProteomicsPublishingQuality ControlResourcesRoleSamplingSpecific qualifier valueTechniquesTranslational ResearchTranslationsWorkcancer diagnosiscancer therapycancer typecandidate identificationcandidate markerclinical centerclinical translationclinically relevantcomputerized data processingcomputerized toolsdata integrationdata qualitydeep learningepigenomicsfunctional genomicsgenetic variantgenomic aberrationsgenomic predictorsimprovedinsightmachine learning algorithmnatural languagenovelpatient prognosispredictive modelingprogramsprotein biomarkersproteogenomicssuccesstargeted biomarkertooltool developmenttranscriptomicstreatment responsetumortumor microenvironmentverification and validationweb portalworking group
项目摘要
Project Summary
By combining mass spectrometry (MS)-based proteomics with genomics, epigenomics, and
transcriptomics, proteogenomics holds great potential to better illuminate cancer complexities than individual
‘omes. During the past 10 years, the Clinical Proteomics Tumor Analysis Consortium (CPTAC) has performed
comprehensive proteogenomic characterization of >1,500 tumors across 10 cancer types. These studies not
only yield novel biological and clinical insights into different cancer types but also produce valuable datasets and
computational tools that can be further used by the broad scientific community. The next phase of the CPTAC
program seeks to expand the current success to more cancer types and translational research focusing on
clinically relevant questions. Our integrative proteogenomic data analysis center (iPGDAC) is one of the current
CPTAC funded PGDACs. We have participated in the studies of all CPTAC cancer types and have played a
leading role in data analysis for several cancer types. This application seeks to continue and enhance our
contribution to the next phase of the CPTAC program. The overarching goal of our PGDAC is to accelerate the
translation of cancer proteogenomic data into better understanding of cancer biology and improved cancer
treatment. We will continue developing and improving our computing tools, workflows, and web portals that have
already been successfully used in the CPTAC studies for sequence-based and pathway/network-based
proteogenomic data integration. In addition, we will address unmet needs in post-translational modification
(PTM)-related analyses by using protein sequence and natural language-based deep learning techniques to
improve PTM peptide identification, to predict genomic variant impact on PTMs, and to connect PTM sites to
existing knowledge. Using unique tools from our team and cutting edge statistical inference and machine learning
algorithms, we will perform integrated analysis on proteogenomic data from the CPTAC studies to: 1) create a
comprehensive molecular and cellular portrait for each patient’s tumor; 2) identify and characterize molecular
and tumor microenvironment/immune subtypes; 3) prioritize functional genomic aberrations using
proteogenomic data; 4) reveal molecular mechanisms of cancer phenotypes; and 5) develop predictive models
for patient prognosis and treatment response. Our PGDAC brings to the CPTAC network a fully integrated,
completely established program with expertise in all the critical areas specified by the RFA. We have a proven
track record of leadership in computational proteogenomics and successful collaboration in the CPTAC network,
and we expect to broadly advance the field through this project.
项目总结
项目成果
期刊论文数量(1)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
OmicsEV: a tool for comprehensive quality evaluation of omics data tables.
- DOI:10.1093/bioinformatics/btac698
- 发表时间:2022-12-13
- 期刊:
- 影响因子:0
- 作者:
- 通讯作者:
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
数据更新时间:{{ journalArticles.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ monograph.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ sciAawards.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ conferencePapers.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ patent.updateTime }}
Bing Zhang其他文献
Bing Zhang的其他文献
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
{{ truncateString('Bing Zhang', 18)}}的其他基金
Illuminating understudied druggable proteins using pan-cancer proteogenomics data
使用泛癌蛋白质组学数据阐明尚未研究的可药物蛋白
- 批准号:
10449905 - 财政年份:2022
- 资助金额:
$ 86.41万 - 项目类别:
iPGDAC, An Integrative Proteogenomic Data Analysis Center for CPTAC
iPGDAC,CPTAC 综合蛋白质组数据分析中心
- 批准号:
10440591 - 财政年份:2022
- 资助金额:
$ 86.41万 - 项目类别:
Illuminating understudied druggable proteins using pan-cancer proteogenomics data
使用泛癌蛋白质组学数据阐明尚未研究的可药物蛋白
- 批准号:
10671574 - 财政年份:2022
- 资助金额:
$ 86.41万 - 项目类别:
Proteogenomics-driven therapeutic discovery in hepatocellular carcinoma
蛋白质基因组学驱动的肝细胞癌治疗发现
- 批准号:
10594466 - 财政年份:2020
- 资助金额:
$ 86.41万 - 项目类别:
Proteogenomics-driven therapeutic discovery in hepatocellular carcinoma
蛋白质基因组学驱动的肝细胞癌治疗发现
- 批准号:
10380646 - 财政年份:2020
- 资助金额:
$ 86.41万 - 项目类别:
iPGDAC, An Integrative Proteogenomic Data Analysis Center for CPTAC
iPGDAC,CPTAC 综合蛋白质组数据分析中心
- 批准号:
9764289 - 财政年份:2016
- 资助金额:
$ 86.41万 - 项目类别:
iPGDAC, An Integrative Proteogenomic Data Analysis Center for CPTAC
iPGDAC,CPTAC 综合蛋白质组数据分析中心
- 批准号:
9210303 - 财政年份:2016
- 资助金额:
$ 86.41万 - 项目类别:
相似海外基金
Rational design of rapidly translatable, highly antigenic and novel recombinant immunogens to address deficiencies of current snakebite treatments
合理设计可快速翻译、高抗原性和新型重组免疫原,以解决当前蛇咬伤治疗的缺陷
- 批准号:
MR/S03398X/2 - 财政年份:2024
- 资助金额:
$ 86.41万 - 项目类别:
Fellowship
CAREER: FEAST (Food Ecosystems And circularity for Sustainable Transformation) framework to address Hidden Hunger
职业:FEAST(食品生态系统和可持续转型循环)框架解决隐性饥饿
- 批准号:
2338423 - 财政年份:2024
- 资助金额:
$ 86.41万 - 项目类别:
Continuing Grant
Re-thinking drug nanocrystals as highly loaded vectors to address key unmet therapeutic challenges
重新思考药物纳米晶体作为高负载载体以解决关键的未满足的治疗挑战
- 批准号:
EP/Y001486/1 - 财政年份:2024
- 资助金额:
$ 86.41万 - 项目类别:
Research Grant
Metrology to address ion suppression in multimodal mass spectrometry imaging with application in oncology
计量学解决多模态质谱成像中的离子抑制问题及其在肿瘤学中的应用
- 批准号:
MR/X03657X/1 - 财政年份:2024
- 资助金额:
$ 86.41万 - 项目类别:
Fellowship
CRII: SHF: A Novel Address Translation Architecture for Virtualized Clouds
CRII:SHF:一种用于虚拟化云的新型地址转换架构
- 批准号:
2348066 - 财政年份:2024
- 资助金额:
$ 86.41万 - 项目类别:
Standard Grant
The Abundance Project: Enhancing Cultural & Green Inclusion in Social Prescribing in Southwest London to Address Ethnic Inequalities in Mental Health
丰富项目:增强文化
- 批准号:
AH/Z505481/1 - 财政年份:2024
- 资助金额:
$ 86.41万 - 项目类别:
Research Grant
ERAMET - Ecosystem for rapid adoption of modelling and simulation METhods to address regulatory needs in the development of orphan and paediatric medicines
ERAMET - 快速采用建模和模拟方法的生态系统,以满足孤儿药和儿科药物开发中的监管需求
- 批准号:
10107647 - 财政年份:2024
- 资助金额:
$ 86.41万 - 项目类别:
EU-Funded
BIORETS: Convergence Research Experiences for Teachers in Synthetic and Systems Biology to Address Challenges in Food, Health, Energy, and Environment
BIORETS:合成和系统生物学教师的融合研究经验,以应对食品、健康、能源和环境方面的挑战
- 批准号:
2341402 - 财政年份:2024
- 资助金额:
$ 86.41万 - 项目类别:
Standard Grant
Ecosystem for rapid adoption of modelling and simulation METhods to address regulatory needs in the development of orphan and paediatric medicines
快速采用建模和模拟方法的生态系统,以满足孤儿药和儿科药物开发中的监管需求
- 批准号:
10106221 - 财政年份:2024
- 资助金额:
$ 86.41万 - 项目类别:
EU-Funded
Recite: Building Research by Communities to Address Inequities through Expression
背诵:社区开展研究,通过表达解决不平等问题
- 批准号:
AH/Z505341/1 - 财政年份:2024
- 资助金额:
$ 86.41万 - 项目类别:
Research Grant