三月week4文献阅读4：Biological Databases for Hematology Research
血液学研究生物数据库
Abstract
With the advances of genome-wide sequencing technologies and bioinformatics approaches, a large number of datasets of normal and malignant erythropoiesis have been generated and made public to researchers around the world.
随着全基因组测序技术和生物信息学方法的进步，大量的正常和恶性红细胞生成数据集已经产生并向世界各地的研究人员公开。
Collection and integration of these datasets greatly facilitate basic research and clinical diagnosis and treatment of blood disorders.
这些数据集的收集和集成极大地促进了血液疾病的基础研究和临床诊断与治疗。
Here we provide a brief introduction of the most popular omics data resources of normal and malignant hematopoiesis, including some integrated web tools, to help users get better equipped to perform common analyses.
在这里，我们简要介绍了最流行的正常和恶性造血组学数据资源，包括一些集成的web工具，以帮助用户更好地进行常见的分析。
We hope this review will promote the awareness and facilitate the usage of public database resources in the hematology research.
我们希望这篇综述能提高对血液学研究中公共数据库资源的认识和利用。
KEYWORDS
Hematology;Hematological diseases;Omics data resources;Database;Bioinformatics
血液学;血液学疾病;组学数据资源;数据库;生物信息学
Introduction
Disorders of blood system lead to different kinds of hematological diseases in millions of people every year globally.
血液系统紊乱每年导致全球数百万人罹患不同种类的血液病。
Blood cells consist of three types of cells, namely erythrocytes (red blood cells, RBCs), leukocytes (white blood cells), and thrombocytes (platelets),all of which are differentiated and developed from hematopoietic stem cells (HSCs).
血细胞由红细胞(红细胞，红细胞)、白细胞(白细胞)和血小板(血小板)三种类型的细胞组成，它们都是由造血干细胞(HSCs)分化和发育而来的。
Erythropoiesis normally produces functional RBCs [1], whereas erroneous erythropoiesis would lead to anemia, leukemia, and other blood diseases [2].
红细胞生成通常产生功能性红细胞[1]，而错误的红细胞生成会导致贫血、白血病和其他血液疾病[2]。
In particular, single-cell sequencing technology makes it feasible to trace the HSC specification, cell fate decision, and differentiation into various cell types at single-cell resolution [3,4].
特别是，单细胞测序技术使得在单细胞分辨率下追踪HSC分化、细胞命运决定以及分化成各种细胞类型成为可能[3,4]。
In addition, high-throughput sequencing also allows genome-wide analysis of transcription factor binding and histone modifications by chromatin immunoprecipitation sequencing (ChIP-seq) [5], identification of open regions of chromatin by DNase-Seq [5], as well as transcriptomic expression profiles by RNA-Seq [5].
此外，高通量测序还允许染色质免疫沉淀测序(ChIP-seq)[5]对转录因子结合和组蛋白修饰进行全基因组分析，dnas -seq[5]对染色质开放区域进行识别，RNA-Seq[5]对转录组表达谱进行分析。
Deeper understanding of the hematological processes of mammals has been driven by the development of these technologies [6].
这些技术的发展推动了对哺乳动物血液学过程的深入了解。
Large organizations, such as the National Center for Biotechnology Information (NCBI), and projects collaborated by international research groups, for example the Encyclopedia of DNA Elements (ENCODE), and a variety of individual laboratories have produced and released many genome-wide datasets to public [7].
大型组织，如国家生物技术信息中心(NCBI)，以及由国际研究小组合作的项目，例如DNA元素百科全书(ENCODE)，以及各种单独的实验室，已经制作并向公共[7]发布了许多全基因组的数据集。
Thanks to the increasingly deeper interpretation of the human genome and the development of bioinformatics databases, we have now appreciated the human erythropoiesis more.
随着人类基因组解释的日益深入和生物信息学数据库的发展，我们对人类红细胞生成有了更多的认识。
Here we collect the most popular omics data resources of normal and malignant hematopoiesis (Table 1). These data components and some integrated web tools for common analyses are introduced in this review
在这里，我们收集了最流行的正常和恶性造血组学数据资源(表1)。本文介绍了这些数据组件和一些用于常见分析的集成web工具.
Table 1 Main biological databases for hematology research.
| Name | Weblink | Main features | Cell type | Data type | Refs. |
|---|---|---|---|---|---|
| European LeukemiaNet | http://www.leukemia-net.org/content/home/index_eng.html | Providing physicians and patients research information about diagnosis, treatment, and ongoing clinical trials, as well as further information about leukemia为医生和患者提供关于诊断、治疗和正在进行的临床试验的研究信息，以及关于白血病的进一步信息 | Clinical data of leukemia patient | Clinical data | [8] |
| Red Cell Membrane Disorder Mutations Database红细胞膜异常突变数据库 | http://research.nhgri.nih.gov/RBCmembrane | Grouping all mutation genes occurring in single or more kinds of inherited disorders of the erythrocyte membrane associated with hemolytic anemia将发生于溶血性贫血的单个或多个遗传性疾病的所有突变基因分组 | RBCs of hereditary spherocytosis, hereditary elliptocytosis, and hereditary pyropoikilocytosis patients遗传性球形红细胞增多症、遗传性椭圆形红细胞增多症和遗传性焦红细胞增多症患者的红细胞计数 | Mutation information of related genes | [9] |
| dbRBC | http://www.ncbi.nlm.nih.gov/projects/gv/rbc/main.fcgi?cmd=nit | Providing DNA and clinical data related to the human RBCs, integrated with BGMUT database documenting variations in genes that encode antigens for human blood groups提供与人类红细胞相关的DNA和临床数据，并与BGMUT数据库集成，该数据库记录了编码人类血型抗原的基因的变异 | Human RBCs人类红细胞表面 | DNA and clinical data | [10] |
| CODEX | http://codex.stemcells.cam.ac.uk | Containing a subunit database HAEMCODE specialized for grouping NGS data of human and mouse hematopoietic cell experiments包含一个亚单位数据库血细胞HAEMCODE专门为分组的NGS数据的人和小鼠造血细胞实验 | Human and mouse hematopoietic cells人和小鼠造血细胞 | NGS data | [11] |
| ErythronDB | http://www.cbil.upenn.edu/ErythronDB | Providing expression profile of murine primitive and definitive erythroid cells, and supporting gene searching with annotation, differential expression, transcriptional regulation, etc.提供小鼠原始和确定的红细胞表达谱，并通过注释、差异表达、转录调控等支持基因搜索。 | Murine primitive and definitive erythroid cells | Gene expression data | [12] |
| Hembase | http://hembase.niddk.nih.gov/ | Integrating sequencing data of ESTs of human erythroid cells, differentiated erythrocytes, and mature RBCs整合人红细胞、分化红细胞和成熟红细胞est测序数据 | Human erythroid cells,differentiated erythrocytes, and | ||
| mature RBCs | EST data | [1] | |||
| BloodSpot | http://www.bloodspot.eu | Providing gene expression profiles of healthy and malignant hematopoiesis in human or mice, encompassing more than 5000 samples in total提供人类或小鼠健康和恶性造血的基因表达谱，共包含5000多个样本 | Human or mouse hematopoietic cells | Oligonucleotide microarray chip data and RNA-seq data寡核苷酸芯片数据和RNA-seq数据 | [15] |
| BloodChIP | http://www.med.unsw.edu.au/CRCWeb.nsf/page/BloodChIP | Exploring and visualizing TF sites in human CD34+ and other normal and leukemic cells based on TF ChIP-seq data基于TF ChIP-seq数据，探索和可视化人CD34+及其他正常和白血病细胞中的TF位点 | Human CD34+ and leukemic cells人类CD34+和白血病细胞 | Gene expression data,histone ChIP-seq data,DNase-seq data, and digital genomic footprinting data基因表达数据，组蛋白芯片seq数据，dnas -seq数据，数字基因组印迹数据 | [17] |
| Leukemia Gene Atlas | http://www.leukemia-gene-atlas.org/LGAtlas | Integrating datasets from more than 5800 leukemia and hematopoiesis samples sequenced by microarray, DNA methylation, SNP, and high-throughput sequencing整合来自5800多个白血病和造血样本的数据集，通过微阵列、DNA甲基化、SNP和高通量测序进行测序 | Clinical leukemia samples | Microarray, DNA methylation, and SNP data | [19] |
| DBA mutation database | http://www.dbagenes.unito.it | Integrating information on DBA mutation genes and changes of DNA, RNA, protein, and the frequency of the mutation整合DBA突变基因和DNA、RNA、蛋白质变化以及突变频率的信息 | Blood cells of DBA | General information on variants of all DBA-related genes所有dba相关基因变异的一般信息 | [23,14] |
Note: ErythronDB, the Erythron Database; ChIP, chromatin immunoprecipitation; EST, expressed sequence tag; DBA, Diamond-Blackfan anemia; BGMUT, Blood Group Antigen Gene Mutation
Database; NGS, next-generation sequencing; RBC, red blood cell; SNP, single nucleotide polymorphism; TF, transcription factor.
注:ErythronDB, Erythron数据库;ChIP,染色质免疫沉淀反应;EST，表示序列标记;DBA, Diamond-Blackfan贫血;BGMUT，血型抗原基因突变数据库;NGS,下一代测序;RBC:红细胞;SNP:单核苷酸多态性;TF,转录因子。
European LeukemiaNet
Leukemia is a cancer of white blood cells with high incidence among all ages.
白血病是一种高发于各个年龄段的白细胞癌。
To centralize the fragmented information of European leukemia, the European LeukemiaNet (ELN) was founded by the 6th Framework Program of the European Community in 2004 [8].
为了集中欧洲白血病的碎片化信息，欧洲白血病网络(ELN)于2004年由欧洲共同体第六届框架计划[8]建立。
The website with friendly user interface delivers information about ongoing clinical trials to physicians and patients, as well as further information regarding leukemia research, such as via publishing study protocols.
该网站具有友好的用户界面，为医生和患者提供正在进行的临床试验的信息，以及关于白血病研究的进一步信息，如通过发布研究协议。
Meanwhile, ELN shares knowledge about study design and monitoring, as well as data management and analysis, and pushes forward the discussion on leukemia within Europe (http://www.leukemia-net.org/content/home/index_eng.html).
与此同时，ELN分享了关于研究设计和监测、数据管理和分析的知识，并推动了关于欧洲白血病的讨论(http://www.leukemia-net.org/content/home/index_eng.html)。
As many as 17 work packages work separately on information integration about research, diagnosis, and treatment of leukemia.
多达17个工作包分别致力于白血病研究、诊断和治疗的信息集成。
Furthermore, ELN also provides information for patients and physicians to better understand the leukemia, the diagnostic methods, and different therapies available.
此外，ELN还为患者和医生提供信息，以更好地了解白血病、诊断方法和不同的治疗方法。
Red Cell Membrane Disorder Mutations Database
Red cell membrane inherited disorders involves either altered membrane structural organization or altered membrane transport function [9].
红细胞膜遗传性疾病包括改变细胞膜结构组织或改变细胞膜转运功能[9]。
The Red Cell Membrane Disorder Mutations Database (http://research.nhgri.nih.gov/RBCmembrane/) contains the mutations associated with three major inherited blood disorders, namely hereditary spherocytosis, elliptocytosis, and pyropoikilocytosis, all of which are caused by the disorder of red cell membrane structural organization.
红细胞膜异常突变数据库(http://research.nhgri.nih.gov/RBCmembrane/)包含了与遗传性球形红细胞增多症、椭圆形红细胞增多症和热解红细胞增多症这三种主要遗传性血液疾病相关的突变，这些突变都是由红细胞膜结构组织紊乱引起的。
The welcome page introduces the gene mutations associated with the three diseases, as well as the term linkages to the Online Mendelian Inheritance in Man (OMIM) database for related genes.
欢迎页面介绍了与这三种疾病相关的基因突变，以及与相关基因的在线孟德尔遗传(OMIM)数据库相关的术语链接。
This database provides detailed information of gene mutations occurring in one or more diseases in its submenu.
该数据库在其子菜单中提供了发生在一种或多种疾病中的基因突变的详细信息。
In other submenus, users can also obtain additional detailed information about clinical research program and genetic counseling from the National Human Genome Research Institute (NHGRI), the United States.
在其他子菜单中，用户还可以从美国国家人类基因组研究所(NHGRI)获得更多关于临床研究计划和遗传咨询的详细信息。
In addition, the submenus also provide the linkage to the University of California Santa Cruz (UCSC) database for some mutation genes.
此外，子菜单还提供了与加州大学圣克鲁兹分校(UCSC)数据库的一些突变基因的链接。
At the bottom of the menu, researchers can find the contact information if they have additions, updates, or descriptions of new mutations.
在菜单的底部，研究人员可以找到联系信息，如果他们有补充，更新，或描述新的突变。
dbRBC
The dbRBC database is one of the NCBI database resources that provides an integrated and freely-accessible platform for DNA sequencing data and clinical data associated with the human RBCs (http://www.ncbi.nlm.nih.gov/projects/gv/rbc/main.fcgi?cmd=init).
dbRBC数据库是NCBI数据库资源之一，它为与人类体红细胞RBC相关的DNA测序数据和临床数据提供了一个集成的、可自由访问的平台(http://www.ncbi.nlm.nih.gov/projects/gv/rbc/main.fcgi?cmd=init).
It integrates the data from the Blood Group Antigen Gene Mutation Database (BGMUT) that records variations in genes encoding antigens for human blood groups from the NCBI [10].
它整合了来自血型抗原基因突变数据库(BGMUT)的数据，该数据库记录了来自NCBI[10]的人类血型抗原编码基因的变异
Users could obtain the data from the download menu that directly links to the page of file transfer protocol.
用户可以从直接链接到文件传输协议页面的下载菜单中获取数据。
dbRBC homepage also offers the linkage to the parallel resources, such as dbMHC for data related to the human major histocompatibility complex (MHC) and dbLRC for resource available for human leukocyte receptor complex (LRC).
dbRBC主页还提供了与并行资源的链接，例如用于人类主要组织相容性复合体(MHC)的数据的dbMHC和用于人类白细胞受体复合体(LRC)的资源的dbLRC。
These 3 public resources make up the database cluster for routine clinical applications [11], such as the ABO genotyping technology.
这3种公共资源构成了常规临床应用的数据库集群，如ABO基因分型技术。
Some additional practical tools are also provided, such as the Alignment Viewer and Primer Resource.
还提供了一些其他实用工具，如对Alignment Viewer(齐查看器)和Primer Resource(入门资源 )。
CODEX
CODEX (http://codex.stemcells.cam.ac.uk/) is a database of mouse and human NGS experiments.
CODEX (http://codex.stemcells.cam.ac.uk/)是一个关于小鼠和人类NGS实验的数据库。
The aim of CODEX is to provide an open-resource of NGS experiments processed by uniform procedures.
CODEX 委员会的目的是提供一种采用统一程序处理的NGS实验的开放资源。
In this database, metadata of human and mouse samples from hematological experiments are collected and sequencing data are uniformly processed and vetted [12].
该数据库收集血液学实验中人类和小鼠样本的元数据，并对测序数据进行统一处理和审核。
CODEX also provides access to processed and curated NGS experiments, including ChIP-seq, RNA-seq, and DNase-seq.
CODEX 还提供了加工和管理NGS实验的途径，包括ChIP-seq、RNA-seq和dnas -seq。
The main data sources of CODEX are NGS repositories, for instance, the Gene Expression Omnibus (GEO) and ArrayExpress.
CODEX的主要数据源是NGS知识库，如基因表达综合数据库(GEO)和ArrayExpress。
Besides, CODEX also provides a private site hosting non-published data.
此外，CODEX还提供了一个托管非公开数据的私有站点。
Furthermore, processed datasets can be analyzed online or downloaded.
此外，处理后的数据集可以在线分析或下载。
CODEX now covers data on 133 hematopoietic cells and embryonic stem cells, and 269 factors associated with these cells.
CODEX现在涵盖了133个造血细胞和胚胎干细胞的数据，以及与这些细胞相关的269个因子。
The Erythron Database
The Erythron Database (ErythronDB;http://www.cbil.upenn.edu/ErythronDB) was built to facilitate access to erythroid expression data and the analysis results in murine primitive and definitive erythroid cells [13].
建立Erythron数据库(ErythronDB;http://www.cbil.upenn.edu/ErythronDB)是为了方便获取小鼠原始和确定的红细胞[13]中的红细胞表达数据和分析结果。
ErythronDB allows users to identify differentially-expressed genes and custom-made downstream analysis in the strategy module.
ErythronDB允许用户在策略模块中识别差异表达的基因和定制的下游分析。
Users are also permitted to save and share strategies with other registered users.
用户还可以与其他注册用户保存和共享策略。
The database integrates global gene expression profile data of primitive, fetal liver definitive, and adult bone marrow definitive erythroid using Affymetrix array for each maturation stage.
该数据库使用Affymetrix阵列对每个成熟阶段的原始、胎儿肝脏和成年骨髓红细胞的全球基因表达谱数据进行了整合。
ErythronDB supports complex investigations on expression parameters, as well as the Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) annotations.
ErythronDB支持对表达参数的复杂研究，以及基因本体(GO)和 Kyoto基因和基因组百科全书(KEGG)注释。
To ensure abundant knowledge on mouse genes, ErythronDB displays links to external databases, including the Mouse Genome Informatics (MGI).
为确保对小鼠基因有丰富的知识，ErythronDB显示到外部数据库的链接，包括小鼠基因组信息学(MGI)。
Hembase
Hembase (http://hembase.niddk.nih.gov) provides genomebased access to human genes transcribed during erythropoiesis.
Hembase (http://hembase.niddk.nih.gov)提供了对红细胞生成过程中转录的人类基因的基于基因组的访问。
By sequencing several thousand expressed sequence tags (ESTs) of human erythroid cells, including progenitor cells, precursor cells, and mature RBCs, the Hembase integrated these data to provide users a friendly browser and the genome portal.
Hembase通过对人类红细胞(包括祖细胞、前体细胞和成熟红细胞)的数千个表达序列标记(est)进行测序，整合了这些数据，为用户提供一个友好的浏览器和基因组门户。
To date, the database contained 15,752 entries of ESTs and 380 genes associated with erythropoiesis [1].
到目前为止，数据库包含了15,752个红细胞和380个与红细胞生成相关的基因。
Hembase provides cytogenetic band position as well as a unique name as concise annotations for each search entry.
Hembase为每个搜索条目提供了细胞遗传带位置以及唯一的名称和简洁的注释。
Users can search by gene name, keywords, or cytogenetic location.
用户可以通过基因名称、关键字或细胞遗传学位置搜索。
All the sequencing information in Hembase can be used without registration, and all ESTs can be downloaded from the NCBI UniGene Library Browser [14].
无需注册即可使用Hembase中的所有排序信息，所有ESTs都可以从NCBI UniGene库浏览器[14]下载。
BloodSpot
BloodSpot (http://www.bloodspot.eu) is a database including gene expression profiles of healthy and malignant hematopoiesis in humans or mice, which had been generated by oligonucleotide microarray chips and RNA sequencing [15].
BloodSpot (http://www.bloodspot.eu)是由寡核苷酸芯片和RNA测序[15]生成的人类或小鼠健康和恶性造血基因表达谱数据库。
This platform is an improvement and expansion of HemaExplorer and encompasses more than 5000 samples in total [16].
这个平台是HemaExplorer的改进和扩展，包含了超过5000个[16]样本。
For each query gene or gene signature, BloodSpot provides three concomitant levels of visualization—gene expression, survival plot, and hierarchical tree of samples.
对于每个查询基因或基因签名，BloodSpot提供了三个伴随的可视化级别——基因表达、生存图和样本的层次树。
Besides, BloodSpot also contains other built-in tools such as exploring the top correlated genes and calculating the student t-test significance between pairs of populations in the default expression plot.
此外，BloodSpot还包含其他内置工具，如在默认表达图中探索最相关的基因，计算成对群体间的student t检验显著性。
Another feature of BloodSpot is BloodPool, an assembled and integrated database collecting the results of multiple studies with more than 2000 samples focusing on acute myeloid leukemia (AML).
BloodSpot的另一个特点是血池，这是一个汇集和集成的数据库，收集了2000多个以急性髓系白血病(AML)为重点的多个研究的结果。
BloodChIP
The BloodChIP database (http://www.med.unsw.edu.au/CRCWeb.nsf/page/BloodChIP) provides a user-friendly exploration and visualization of transcription factor (TF)binding sites in human CD34+ and leukemia cells produced by TF ChIP-Seq platform [17].
BloodChIP数据库(http://www.med.unsw.edu.au/CRCWeb.nsf/page/BloodChIP)提供了对人CD34+和TF ChIP-Seq平台[17]产生的白血病细胞中转录因子(TF)结合位点的友好探索和可视化。
Users can enter the keywords about specific gene(s) or genomic region(s) to retrieve TF binding profiles.
用户可以输入关于特定基因或基因组区域的关键字来检索TF结合谱。
Users can also search all the target genes for a combination of selected TFs or for any selected TFs in specific cell type(s).
用户还可以搜索所有目标基因，以寻找所选TFs的组合或特定细胞类型的任何所选TFs。
Currently, BloodChIP covers data on four cell types, i.e.,CD34+ hematopoietic stem and progenitor cells (HSPCs), megakaryocytes, SKNO-1, and K562.
目前，BloodChIP涵盖了四种细胞类型的数据，即、CD34+造血干细胞、巨核细胞、SKNO-1、K562。
To maximize the utility of these data, this database has been integrated with many public data for insights into the transcriptional regulation of query genes, such as gene expression data, histone ChIP-seq data, and DNase-seq data from the Human Epigenome Atlas and ENCODE database [7,18].
为了最大限度地利用这些数据，该数据库已与许多公共数据集成，深入了解查询基因的转录调控，如基因表达数据、组蛋白ChIP-seq数据、人类表观基因组图谱和编码数据库中的dnas -seq数据等[7,18]。
Leukemia Gene Atlas
Leukemia Gene Atlas (LGA) database is a public platform integrating diverse genomic data published in the leukemia field [19].
白血病基因图谱(LGA)数据库是一个公共平台，集成了白血病领域发表的多种基因组数据。
The LGA supports comprehensive research, analysis, and browse functions for more than 5800 leukemia and hematopoiesis samples sequenced by multiple platforms, such as microarray, DNA methylation, SNP, and other highthroughput sequencing manners.
LGA支持对5800多个白血病和造血样本进行综合研究、分析和浏览功能，这些样本由多个平台测序，如微阵列、DNA甲基化、SNP等高通量测序方式。
The database contains information on studies from various aspects, such as prediction of molecular subtypes of leukemia, human hematopoiesis, and TF binding sites imported from the GEO.
该数据库包含了来自各个方面的研究信息，如白血病分子亚型的预测、人类造血、从GEO导入的TF结合位点等。
LGA also has established quality control procedure to filter out qualified data imported from other datasets.
LGA还建立了质量控制程序，过滤从其他数据集导入的合格数据。
Results of each study include differentially-expressed genes, GO annotations, copy number alterations, and an extract of the Catalogue of Somatic Mutations in Cancer (COSMIC) database.
每项研究的结果包括差异表达的基因、GO注释、拷贝数改变，以及癌症(COSMIC)数据库中体细胞突变目录的摘录。
The LGA database is freely accessible at http://www.leukemia-gene-atlas.org/LGAtlas/.
LGA数据库可在http://www.leukemia-gene-atlas.org/LGAtlas/.。
Diamond-Blackfan anemia mutation database
Diamond-Blackfan anemia (DBA) is a hereditary bone marrow failure syndrome characterized by the marked heterogeneity of clinical symptom, such as anemia, developmental abnormalities, and an increased risk of malignancy [20–22].
Diamond-Blackfan贫血(DBA)是一种遗传性骨髓衰竭综合征，临床症状具有明显的异质性，如贫血、发育异常、恶性肿瘤风险增加等[20-22]。
The DBA mutation database was built aimed to help researchers and physicians to better understand the mutations found in patients.
DBA突变数据库的建立是为了帮助研究人员和医生更好地了解在患者中发现的突变。
This database is based on the Leiden Open Variation Database (LOVD) system (http://www.dbagenes.unito.it).
该数据库基于莱顿开放变异数据库(LOVD)系统(http://www.dbagenes.unitoit)。
The database comprises of 27 published mutations in RPS11 gene, the main contributor to DBA.
数据库由27个已发表的RPS11基因突变组成，RPS11基因是DBA的主要贡献者。
Each mutation is described in detail with both tables and graphs, including gene information,sequence information, and graphic displays from UCSC [23,24].
每个突变都用表格和图表详细描述，包括UCSC的基因信息、序列信息和图形显示[23,24]。
The database provides information on changes in DNA, RNA, and protein, as well as the frequency of the mutations via a convenient search interface.
该数据库通过一个方便的搜索界面提供有关DNA、RNA和蛋白质变化以及突变频率的信息。
Users are welcome to submit mutations after they register as a submitter.
欢迎用户注册为提交者后提交突变。
Concluding remarks
结束语
Due to the recent technological advances, a large amount of data for erythrocyte differentiation has been generated, producing valuable resources for understanding pathogenesis.
近年来，由于技术的进步，产生了大量的红细胞分化数据，为了解其发病机制提供了宝贵的资源。
This review offers a brief introduction of multiple databases in the fields of hematopoiesis and blood diseases (Figure 1), all of which are freely available without any registration.
这篇综述简要介绍了造血和血液疾病领域的多个数据库(图1)，所有这些数据库都是免费提供的，没有任何注册。
The majority of databases, namely Red Cell Membrane Disorder Mutations Database, dbRBC,CODEX, ErythronDB, Hembase, BloodSpot, and BloodChIP focus on the normal erythrocyte development in humans and model organisms to provide transcriptomic and genomic data.
大多数数据库，即红细胞膜功能紊乱突变数据库、dbRBC、CODEX、ErythronDB、Hembase、BloodSpot、BloodChIP等，关注人类和模型生物红细胞的正常发育，提供转录组和基因组数据。
On the other hand, ELN and LGA are databases in the field of leukemia with clinical resources,whereas DBA mutation database is specifically designed for DBA.
另一方面，ELN和LGA是白血病领域具有临床资源的数据库，而DBA突变数据库是专门为DBA设计的。
Obviously, despite our efforts on hematopoiesis studies, the sample sizes covered in the databases reviewed in this article are still limited and there is also lack of databases for other blood diseases.
显然，尽管我们在造血研究方面做出了努力，但本文所综述的数据库所涵盖的样本量仍然有限，其他血液疾病的数据库也缺乏。
Fortunately, benefiting from big data programs across the globe, people are getting aware of the importance of biological data to public health, which makes it easier for researchers to obtain data generated from a large number of patients or donors.
幸运的是，得益于全球范围内的大数据项目，人们开始意识到生物数据对公共健康的重要性，这使得研究人员更容易获取大量患者或捐赠者的数据。
With the accumulation of knowledge and research progress,The 10 database mentioned in the current review are classified into 3 categories.
随着知识的积累和研究的进展，本综述中提到的10个数据库被分为三类。
Four databases marked with red petals on the left side of the flower are disease databases, providing biological data of hematopoietic disorders.
在花的左侧用红色花瓣标记的四个数据库是疾病数据库，提供造血疾病的生物学数据。
Another four databases marked with blue petals on the right side of the flower are hematopoiesis database, providing information on normal hematopoietic development.
另外四个在花的右侧用蓝色花瓣标记的数据库是造血数据库，提供正常造血发育的信息。
The remaining two databases marked in yellow in the center of the flower are integrated databases.
在花的中心用黄色标记的其余两个数据库是集成数据库。
DBA,Diamond Blackfan anemia;ErythronDB, the Erythron Database.
DBA,Diamond Blackfan贫血;ErythronDB, Erythron数据库。
we are expecting to see a number of databases combined with clinical data available for biologists and clinicians in near future.
我们期望在不久的将来看到一些数据库与临床数据相结合，供生物学家和临床医生使用。
Competing interests
相互竞争的利益
The authors declared that there are no competing interests
作者宣称没有相互竞争的利益
Acknowledgments
This study was supported by the National Key Research and Development Program of China (Grant No. 2016YFC0901700), the National High-tech R&D Program of China (863 Program, Grant Nos. 2015AA020101 and 2015AA020108), the National ‘‘12th Five-Year Plan” for Science & Technology Support of China (Grant No. 2013BAI01B09), and the National Natural Science Foundation of China (Grant Nos. 31471115 and 81670109) awarded to XF
本研究支持中国国家重点研发项目(批准号2016 yfc0901700),中国国家高科技研发计划(863计划,批准号。2015 aa020101和2015 aa020108),国家“十二五计划”中国科学与技术支持(批准号2013 bai01b09),以及中国的国家自然科学基金(批准号31471115和31471115)授予XF
References
文章详情 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5200935/
方向：
准备着手一个红系数据库的开发，看看类似的数据库都是怎么些什么设计：
思考问题：
数据类别：疾病数据库VS 正常造血发育
测序数据：ChIP-seq、RNA-seq和dnas -seq
知识介绍：
功能设计：
目前所有的数据：
与Hembase数据库类似。
正常HSC及其连续