Manually curated database of all conditions with known genetic causes, focusing on medically significant genetic data with available interventions. Includes gene symbol, conditions, allelic conditions, inheritance, age in which interventions are indicated, clinical categorization, and general description of interventions/rationale. Contents are intended to describe types of interventions that might be considered. Includes only single gene alterations and does not include genetic associations or susceptibility factors related to more complex diseases.

List of all genomes and accession numbers used for this analysis.

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 29, 2016. Database containing structural annotations for the proteomes of just under 100 organisms. Using data derived from public databases of translated genomic sequences, representatives from the major branches of Life are included: Prokaryota, Eukaryota and Archaea. The annotations stored in the database may be accessed in a number of ways. The help page provides information on how to access the database. 3D-GENOMICS is now part of a larger project, called e-Protein. The project brings together similar databases at three sites: Imperial College London , University College London and the European Bioinformatics Institute . e-Protein''s mission statement is To provide a fully automated distributed pipeline for large-scale structural and functional annotation of all major proteomes via the use of cutting-edge computer GRID technologies. The following databases are incorporated: NRprot, SCOP, ASTRAL, PFAM, Prosite, taxonomy, COG The following eukaryotic genomes are incorporated: Anopheles gambiae, protein sequences from the mosquito genome; Arabidopsis thaliana, protein sequences from the Arabidopsis genome; Caenorhabditis briggsae, protein sequences from the C.briggsae genome; Caenorhabditis elegans protein sequences from the worm genome; Ciona intestinalis protein sequences from the sea squirt genome; Danio rerio protein sequences from the zebrafish genome; Drosophila melanogaster protein sequences from the fruitfly genome; Encephalitozoon cuniculi protein sequences from the E.cuniculi genome; Fugu rubripes protein sequences from the pufferfish genome; Guillardia theta protein sequences from the G.theta genome; Homo sapiens protein sequences from the human genome; Mus musculus protein sequences from the mouse genome; Neurospora crassa protein sequences from the N.crassa genome; Oryza sativa protein sequences from the rice genome; Plasmodium falciparum protein sequences from the P.falciparum genome; Rattus norvegicus protein sequences from the rat genome; Saccharomyces cerevisiae protein sequences from the yeast genome; Schizosaccharomyces pombe protein sequences from the yeast genome

This website contains information about the genomic sequence of parasites. It also contains multiple search engines to search six frame translations of parasite nucleotide databases for motifs, parasite protein databases for motifs, and parasite protein databases for keywords and text terms. * Guide to Internet Access to Parasite Genome Information * Guide to web-based analysis tools * Parasite Genome BLAST Server: Search a range of parasite specific nucleotide sequence databases with your own sequence. * Parasite Proteome Keyword Search Facility: Search parasite protein databases for keywords and text terms * Parasite Proteome Motif Search Facility: Search parasite protein databases for motifs * Parasite Six Frame Translation Motif Search Facility: Search six frame translations of parasite nucleotide databases for motifs * Genome computing resources: A list of ftp and gopher sites where genome computing applications and other resources can be found.

Data sets used for analyzing miscounts.

The most recent list can be found at the IthaGenes website (http://www.ithanet.eu/db/ithagenes?action=glist).

CottonGen (https://www.cottongen.org) is a curated and integrated web-based relational database providing access to publicly available genomic, genetic and breeding data to enable basic, translational and applied research in cotton. Built using the open-source Tripal database infrastructure, CottonGen supersedes CottonDB and the Cotton Marker Database, which includes sequences, genetic and physical maps, genotypic and phenotypic markers and polymorphisms, quantitative trait loci (QTLs), pathogens, germplasm collections and trait evaluations, pedigrees, and relevant bibliographic citations, with enhanced tools for easier data sharing, mining, visualization, and data retrieval of cotton research data. CottonGen contains annotated whole genome sequences, unigenes from expressed sequence tags (ESTs), markers, trait loci, genetic maps, genes, taxonomy, germplasm, publications and communication resources for the cotton community. Annotated whole genome sequences of Gossypium raimondii are available with aligned genetic markers and transcripts. These whole genome data can be accessed through genome pages, search tools and GBrowse, a popular genome browser. Most of the published cotton genetic maps can be viewed and compared using CMap, a comparative map viewer, and are searchable via map search tools. Search tools also exist for markers, quantitative trait loci (QTLs), germplasm, publications and trait evaluation data. CottonGen also provides online analysis tools such as NCBI BLAST and Batch BLAST. This project is funded/supported by Cotton Incorporated, the USDA-ARS Crop Germplasm Research Unit at College Station, TX, the Southern Association of Agricultural Experiment Station Directors, Bayer CropScience, Corteva/Agriscience, Dow/Phytogen, Monsanto, Washington State University, and NRSP10. Resources in this dataset:Resource Title: Website Pointer for CottonGen. File Name: Web Page, url: https://www.cottongen.org/ Genomic, Genetic and Breeding Resources for Cotton Research Discovery and Crop Improvement organized by :

Species (Gossypium arboreum, barbadense, herbaceum, hirsutum, raimondii, others), Data (Contributors, Download, Submission, Community Projects, Archives, Cotton Trait Ontology, Nomenclatures, and links to Variety Testing Data and NCBISRA Datasets), Search options (Colleague, Genes and Transcripts, Genotype, Germplasm, Map, Markers, Publications, QTLs, Sequences, Trait Evaluation, MegaSearch), Tools (BIMS, BLAST+, CottonCyc, JBrowse, Map Viewer, Primer3, Sequence Retrieval, Synteny Viewer), International Cotton Genome Initiative (ICGI), and Help sources (User manual, FAQs).

Also provides Quick Start links for Major Species and Tools.

A database of oncogenes and tumor suppressor genes. Users can search by genes, chromosomes, and keywords. The coAnsensus domain analysis tool functions to identify conserved protein domains and GO terms among selected TAG genes, while the “oncogenic domain analysis” can analyze oncogenic potential of any user-provided protein based on a weighed term frequency table calculated from the TAG proteins. The completion of human genome sequences allows one to rapidly identify and analyze genes of interest through the use of computational approach. The available annotations including physical characterization and functional domains of known tumor-related genes thus can be used to study the role of genes involved in carcinogenesis. The tumor-associated gene (TAG) database was designed to utilize information from well-characterized oncogenes and tumor suppressor genes to facilitate cancer research. All target genes were identified through text-mining approach from the PubMed database. A semi-automatic information retrieving engine was built to collect specific information of these target genes from various resources and store in the TAG database. At current stage, 519 TAGs including 198 oncogenes, 170 tumor suppressor genes, and 151 genes related to oncogenesis were collected. Information collected in TAG database can be browsed through user-friendly web interfaces that provide searching genes by chromosome or by keywords. The “consensus domain analysis” tool functions to identify conserved protein domains and GO terms among selected TAG genes. In addition, the “oncogenic domain analysis” can analyze oncogenic potential of any user-provided protein based on a weighed term frequency table calculated from the TAG proteins. This study was supported by grant from National research program for genomic medicine (NRPGM) and personnel from Bioinformatics Center of Center for Biotechnology and Biosciences in the National Cheng Kung University, Taiwan.

Yeast is commonly utilized in molecular and cell biology research, and Yarrowia lipolytica is favored by bio-engineers due to its ability to produce copious amounts of lipids, chemicals, and enzymes for industrial applications. Y. lipolytica is a dimorphic yeast that can proliferate in aerobic and hydrophobic environments conducive to industrial use. However, there is limited knowledge about the basic molecular biology of this yeast, including how the genome is duplicated and how gene silencing occurs. Genome sequences of Y. lipolytica strains have offered insights into the genetic basis of this yeast species and have facilitated the development of new industrial applications. Although previous studies have reported the genome sequence of a few Y. lipolytica strains, it is of value to have more precise sequences and annotation, particularly for studies of the biology of this yeast. To further study and characterize the molecular biology of this microorganism, a high-quality reference genome assembly and annotation has been produced for two related Y. lipolytica strains of the opposite mating type, MATA (E122) and MATB (22301-5). The combination of short-read and long-read sequencing of genome DNA and short-read and long-read sequencing of transcript cDNAs allowed the genome assembly and a comparison with a distantly related Yarrowia strain.

DNA Database Management Market Outlook

According to our latest research, the global DNA Database Management market size reached USD 1.92 billion in 2024, reflecting robust demand across forensic, healthcare, and research sectors. The market is demonstrating a strong growth trajectory, with a CAGR of 13.2% projected from 2025 to 2033. By 2033, the DNA database management market is forecasted to attain a value of USD 5.43 billion. This growth is primarily driven by the increasing adoption of DNA analysis in criminal investigations, rising healthcare applications in personalized medicine, and the expanding role of genomic databases in academic research and diagnostics.

One of the foremost growth factors propelling the DNA database management market is the rapid technological advancement in sequencing technologies and bioinformatics platforms. The cost of DNA sequencing has plummeted over the past decade, making large-scale DNA data collection and storage more feasible for both public and private institutions. The integration of artificial intelligence and machine learning into DNA database management systems has further enhanced the speed and accuracy of data analysis, enabling more effective use in applications such as population genomics, ancestry tracing, and disease prediction. The growing need for efficient data management solutions to handle the exponential increase in genomic data is pushing organizations to invest in advanced DNA database management systems, thereby fueling market expansion.

Another key driver is the surge in demand for DNA-based solutions in law enforcement and forensic science. Governments across the globe are increasingly leveraging DNA databases to solve crimes, identify missing persons, and exonerate the innocent. The implementation of national DNA databases in countries such as the United States, United Kingdom, and China has significantly enhanced the ability of law enforcement agencies to link suspects to crime scenes and resolve cold cases. Additionally, the rising incidence of cyber and bio-crimes has necessitated robust and secure DNA database management systems, which are capable of maintaining data integrity and privacy. This trend is expected to intensify as regulatory bodies introduce more stringent guidelines for DNA data storage, access, and sharing, further boosting market growth.

The healthcare and diagnostics sector is also playing a pivotal role in the expansion of the DNA database management market. The proliferation of personalized medicine, pharmacogenomics, and rare disease diagnostics has underscored the importance of comprehensive genomic databases. Hospitals, clinics, and research institutions are increasingly adopting DNA database management solutions to streamline patient data, facilitate research collaborations, and enhance clinical decision-making. The COVID-19 pandemic further accelerated the adoption of genomic surveillance and database management tools to track viral mutations and support public health initiatives. As healthcare systems continue to digitize and integrate genomic information into electronic health records, the demand for scalable and interoperable DNA database management platforms is set to rise.

From a regional perspective, North America leads the DNA database management market, accounting for the largest revenue share in 2024. This dominance is attributed to the presence of advanced healthcare infrastructure, significant government funding for forensic and biomedical research, and the widespread adoption of cutting-edge IT solutions. Europe follows closely, driven by robust regulatory frameworks and collaborative research initiatives across countries. The Asia Pacific region is poised for the fastest growth during the forecast period, fueled by rising investments in biotechnology, increasing awareness of genetic testing, and government initiatives to modernize forensic capabilities. Latin America and the Middle East & Africa, while still emerging, are expected to witness steady growth as they strengthen their healthcare and law enforcement infrastructure.

Collection of curated structural variation in the human genome. Catalogue of human genomic structural variation identified in healthy control samples for studies aiming to correlate genomic variation with phenotypic data. It is continuously updated with new data from peer reviewed research studies. The Database is no longer accepting direct submission of data as they are currently part of a collaboration with two new archival CNV databases at EBI and NCBI, called DGVa and dbVAR, respectively. One of the changes to DGV as part of this collaborative effort is that they will no longer be accepting direct submissions, but rather obtain the datasets from DGVa (short for DGV archive). This will ensure that the three databases are synchronized, and will allow for an official accessioning of variants.

Genomic Selection Platform Market Outlook

According to our latest research, the global Genomic Selection Platform market size reached USD 1.82 billion in 2024, reflecting robust momentum in the adoption of advanced genomic technologies. The market is projected to witness a strong compound annual growth rate (CAGR) of 14.7% from 2025 to 2033, culminating in a forecasted market value of USD 5.8 billion by 2033. This impressive trajectory is primarily fueled by the increasing integration of genomic data analytics in agriculture, animal breeding, and human genomics, alongside expanding investments in precision medicine and biotechnology research.

One of the foremost growth drivers for the Genomic Selection Platform market is the escalating demand for precision breeding in both plant and animal sectors. As global food security concerns intensify and agricultural productivity becomes a critical focus, stakeholders are increasingly turning to genomic selection platforms to accelerate the development of high-yield, disease-resistant crops and livestock. The ability to analyze vast amounts of genetic data and identify desirable traits has revolutionized traditional breeding methods, making them more efficient and predictable. This shift is further supported by government initiatives and public-private partnerships aimed at modernizing agricultural practices, especially in emerging economies where food production challenges are acute.

Another significant factor contributing to market expansion is the surging interest in personalized medicine and human genomics. The declining cost of next-generation sequencing (NGS) technologies and the growing availability of comprehensive genomic databases have enabled healthcare providers and researchers to leverage genomic selection platforms for disease risk assessment, drug discovery, and tailored therapies. Biotechnology companies are increasingly adopting these platforms to streamline research and development processes, reduce time-to-market for new therapeutics, and enhance patient outcomes. The integration of artificial intelligence (AI) and machine learning algorithms with genomic selection tools further amplifies their predictive accuracy, making them indispensable in both clinical and research settings.

Additionally, the continuous evolution of bioinformatics software and cloud-based solutions is propelling the scalability and accessibility of genomic selection platforms. The transition from on-premises to cloud-based deployment models is enabling institutions of all sizes to access powerful computational resources and collaborate on a global scale. This democratization of genomic analysis tools is fostering innovation across academic, commercial, and governmental research institutes. Furthermore, the growing trend of multi-omics integration—combining genomic, proteomic, and metabolomic data—is expanding the utility and value proposition of these platforms, paving the way for holistic approaches to biological research and breeding programs.

Regionally, North America dominates the Genomic Selection Platform market, accounting for the largest share in 2024, followed closely by Europe and Asia Pacific. The presence of leading biotechnology firms, advanced healthcare infrastructure, and substantial public and private investments in genomics research underpin North America's leadership. Meanwhile, Asia Pacific is poised for the highest growth rate over the forecast period, driven by burgeoning agricultural sectors, rising adoption of precision medicine, and supportive regulatory frameworks. Europe continues to play a pivotal role, particularly in plant and animal genomics, supported by robust research networks and funding initiatives. Latin America and the Middle East & Africa are gradually emerging as promising markets, buoyed by increasing awareness and gradual technological adoption.

Component Analysis

The Genomic Selection Platform market by component is segmented into software, hardware, and services, each

Genomic Data Interpretation Services Market Outlook

According to our latest research, the global genomic data interpretation services market size reached USD 2.12 billion in 2024, reflecting robust demand and technological advancements across healthcare and life sciences. The market is expected to grow at a CAGR of 16.8% from 2025 to 2033, driven by expanding clinical applications and increasing adoption of precision medicine. By 2033, the market is forecasted to reach USD 8.16 billion. This remarkable growth is primarily attributed to the surge in genomic sequencing activities, integration of artificial intelligence in data analytics, and the rising need for personalized healthcare solutions globally.

The growth of the genomic data interpretation services market is fundamentally propelled by the exponential increase in genomic sequencing data generated worldwide. As next-generation sequencing (NGS) technologies become more affordable and accessible, healthcare institutions, research bodies, and even direct-to-consumer companies are generating vast amounts of complex genomic data. This data holds immense potential for clinical diagnosis, drug discovery, and personalized treatment plans. However, the interpretation of such high-throughput data requires specialized bioinformatics expertise and advanced analytical tools, creating a burgeoning demand for professional genomic data interpretation services. The integration of machine learning and artificial intelligence algorithms further enhances the accuracy and efficiency of interpretation, making these services indispensable in modern healthcare and research settings.

Another pivotal growth factor for the genomic data interpretation services market is the global shift towards precision medicine and targeted therapies. Governments and private organizations are investing heavily in genomics infrastructure and research, especially in oncology, rare diseases, and pharmacogenomics. The ability to interpret genetic variants and their clinical significance enables healthcare providers to offer tailored treatment regimens, optimize drug efficacy, and minimize adverse drug reactions. This trend is particularly evident in developed markets where regulatory frameworks support genomic testing and reimbursement policies are evolving to include advanced diagnostics. The growing awareness among clinicians and patients about the benefits of genomics-based interventions continues to fuel market expansion.

The increasing collaboration between academia, healthcare providers, and biotechnology companies also plays a significant role in market growth. Strategic partnerships and consortia facilitate the sharing of genomic databases and best practices, accelerating the development of interpretation algorithms and enhancing the quality of insights derived from genomic data. Furthermore, the rise of direct-to-consumer genomic testing has democratized access to genetic information, prompting a surge in demand for user-friendly and reliable interpretation services. However, this growth is accompanied by challenges related to data privacy, standardization, and regulatory compliance, which service providers must navigate to maintain trust and ensure long-term market sustainability.

Regionally, North America dominates the genomic data interpretation services market due to its advanced healthcare infrastructure, significant investments in genomics research, and a high concentration of leading market players. The United States, in particular, benefits from a supportive regulatory environment and widespread adoption of precision medicine initiatives. Europe follows closely, driven by collaborative research efforts and government funding for genomics. The Asia Pacific region is emerging as a high-growth market, fueled by increasing healthcare expenditure, expanding genomic research capabilities, and a growing patient population seeking personalized healthcare solutions. Latin America and the Middle East & Africa are gradually adopting genomic technologies, with localized initiatives and international collaborations contributing to market development in these regions.

Service Type Analysis

The service type segment of the genomic data interpretation services market encompasses Clinical Genomic Interpretation, Research Genomic Interpretation, Direct-to-Consumer Genomic Interpretation, and Others. Clinical Genomic Interpretation services are witnessing the highest demand, primarily due to the

Database of unannotated short single-read primarily genomic sequences from GenBank including random survey sequences clone-end sequences and exon-trapped sequences. The GSS division of GenBank is similar to the EST division, with the exception that most of the sequences are genomic in origin, rather than cDNA (mRNA). It should be noted that two classes (exon trapped products and gene trapped products) may be derived via a cDNA intermediate. Care should be taken when analyzing sequences from either of these classes, as a splicing event could have occurred and the sequence represented in the record may be interrupted when compared to genomic sequence. The GSS division contains (but is not limited to) the following types of data: * random single pass read genome survey sequences. * cosmid/BAC/YAC end sequences * exon trapped genomic sequences * Alu PCR sequences * transposon-tagged sequences Although dbGSS sequences are incorporated into the GSS Division of GenBank, annotation in dbGSS is more comprehensive and includes detailed information about the contributors, experimental conditions, and genetic map locations.

Population Genomic Screening Programs Market Outlook

According to our latest research, the global population genomic screening programs market size reached USD 4.2 billion in 2024, reflecting robust momentum driven by technological advancements and increasing government initiatives worldwide. The market is expected to register a CAGR of 13.5% from 2025 to 2033, propelling the market value to an estimated USD 12.8 billion by 2033. This remarkable growth trajectory is primarily attributed to the expanding implementation of national and regional genomic screening initiatives, heightened awareness regarding personalized medicine, and significant investments in genomics research and infrastructure.

One of the primary growth factors for the population genomic screening programs market is the increasing recognition of genomics as a transformative tool in modern healthcare. Governments and health organizations are increasingly launching large-scale genomic screening programs to detect hereditary diseases, rare genetic disorders, and predispositions to chronic conditions at an early stage. The integration of genomics into routine healthcare enables early intervention, improved disease management, and reduced long-term healthcare costs. Additionally, the declining cost of sequencing technologies, particularly next-generation sequencing (NGS), has made population-scale screening more accessible and economically viable, further accelerating market adoption across diverse healthcare settings.

Another significant driver fueling market expansion is the surge in public-private partnerships and collaborations among research institutes, healthcare providers, and biotechnology companies. These alliances are instrumental in developing comprehensive genomic databases, standardizing screening protocols, and ensuring the ethical use of genetic data. The increasing prevalence of chronic diseases, such as cancer, cardiovascular disorders, and diabetes, has also heightened the demand for population-wide genomic screening programs. By identifying genetic risk factors and enabling personalized prevention strategies, these programs are poised to revolutionize disease prevention and management, ultimately improving population health outcomes.

Furthermore, the growing focus on pharmacogenomics and personalized medicine is catalyzing the adoption of genomic screening programs globally. Pharmaceutical companies and healthcare providers are leveraging population genomic data to optimize drug development, tailor therapies to individual genetic profiles, and minimize adverse drug reactions. The integration of artificial intelligence and big data analytics in genomics research is enhancing the accuracy and predictive power of screening programs, leading to more effective healthcare interventions. As regulatory frameworks evolve to support data privacy and ethical considerations, the market is expected to witness sustained growth, with emerging economies increasingly investing in genomic infrastructure and capacity building.

From a regional perspective, North America dominated the global population genomic screening programs market in 2024, accounting for the largest share due to well-established healthcare infrastructure, significant government funding, and a high prevalence of genetic disorders. Europe followed closely, driven by robust public health initiatives and collaborative research projects. The Asia Pacific region is anticipated to exhibit the fastest growth during the forecast period, supported by rising healthcare expenditures, expanding genomics research, and increasing awareness of personalized medicine. Latin America and the Middle East & Africa are also witnessing gradual market expansion, albeit at a slower pace, as governments and healthcare organizations prioritize genomic research and screening initiatives.

Program Type Analysis

The population genomic screening programs market, when segmented by program type, reveals diverse adoption patterns and growth opportunities across newborn screening

GDR is a curated and integrated web-based relational database. GDR contains comprehensive data of the genetically anchored peach physical map, annotated EST databases of apple, peach, almond, cherry, rose, raspberry and strawberry, Rosaceae maps and markers and all publicly available Rosaceae sequences. Annotations of ESTs include contig assembly, putative function, simple sequence repeats, ORFs, Gene Ontology and anchored position to the peach physical map where applicable. Our integrated map viewer provides graphical interface to the genetic, transcriptome and physical mapping information. We continue to add Rosaceae map data to CMap, a web-based tool that allows users to view comparisons of genetic and physical maps. ESTs, BACs and markers can be queried by various categories and the search result sites are linked to the integrated map viewer or to the WebFPC physical map sites. In addition to browsing and querying the database, users can compare their sequences with the annotated GDR sequences via a dedicated sequence similarity server running either the BLAST or FASTA algorithm, search their sequences for microsatellites using the SSR server or assemble their ESTs using the CAP3 Server.

A database that curates new experimental and bioinformatic information about the genes and gene products of the model bacterium Escherichia coli K-12 strain MG1655. It has been created to integrate information from post-genomic experiments into a single resource with the aim of providing functional predictions for the 1500 or so gene products for which we have no knowledge of their physiological function. While EchoBASE provides a basic annotation of the genome, taken from other databases, its novelty is in the curation of post-genomic experiments and their linkage to genes of unknown function. Experiments published on E. coli are curated to one of two levels. Papers dealing with the determination of function of a single gene are briefly described, while larger dataset are actually included in the database and can be searched and manipulated. This includes data for proteomics studies, protein-protein interaction studies, microarray data, functional genomic approaches (looking at multiple deletion strains for novel phenotypes) and a wide range of predictions that come out of in silico bioinformatic approaches. The aim of the database is to provide hypothesis for the functions of uncharacterized gene products that may be used by the E. coli research community to further our knowledge of this model bacterium.

Background Modern drug discovery is concerned with identification and validation of novel protein targets from among the 30,000 genes or more postulated to be present in the human genome. While protein-protein interactions may be central to many disease indications, it has been difficult to identify new chemical entities capable of regulating these interactions as either agonists or antagonists.

   Results
   In this paper, we show that peptide complements (or surrogates) derived from highly diverse random phage display libraries can be used for the identification of the expected natural biological partners for protein and non-protein targets. Our examples include surrogates isolated against both an extracellular secreted protein (TNFβ) and intracellular disease related mRNAs. In each case, surrogates binding to these targets were obtained and found to contain partner information embedded in their amino acid sequences. Furthermore, this information was able to identify the correct biological partners from large human genome databases by rapid and integrated computer based searches.


   Conclusions
   Modified versions of these surrogates should provide agents capable of modifying the activity of these targets and enable one to study their involvement in specific biological processes as a means of target validation for downstream drug discovery.

(A: Globin-gene causative mutation; B: Disease-modifying mutation; C: Neutral polymorphism).

Generates data for use in developing and refining computational tools for comparing genomic sequence from multiple species. The NISC Comparative Sequencing Program's goal is to establish a data resource consisting of sequences for the same set of targeted genomic regions derived from multiple animal species. The broader program includes plans for a diverse set of analytical studies using the generated sequence and the publication of a series of papers describing the results of those analysis in peer-reviewed journals in a timely fashion. Experimentally, this project involves the shotgun sequencing of mapped BAC clones. For each BAC, an assembly is first performed when a sufficient number of sequence reads have been generated to provide full shotgun coverage of the clone. At that time, the assembled sequence is submitted to the HTGS division of GenBank. Subsequent refinements of the sequence, including the generation of higher-accuracy finished sequence, results in the updating of the sequence record in GenBank. By immediately submitting our BAC-derived sequences to GenBank, it makes their data available as a public service to allow colleagues to speed up their research, consistent with the now well-established routine of sequencing centers participating in the Human Genome Project. However, at the same time, it has made considerable investment in acquiring these mapping and sequence data, including sizable efforts of graduate students, postdoctoral fellows, and other trainees. Furthermore, in most cases, large data sets involving multiple BAC sequences from multiple species must first be generated, often taking many months to accumulate, before the planned analysis can be performed and the resulting papers written and submitted for publication.