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PubMed2006

EST-PAC a web package for EST annotation and protein sequence prediction.

With the decreasing cost of DNA sequencing technology and the vast diversity of biological resources, researchers increasingly face the basic challenge of annotating a larger number of expressed sequences tags (EST) from a variety of species. This typically consists of a series of repetitive tasks, which should be automated and easy to use. The results of these annotation tasks need to be stored and organized in a consistent way. All these operations should be self-installing, platform independent, easy to customize and amenable to using distributed bioinformatics resources available on the Internet. In order to address these issues, we present EST-PAC a web oriented multi-platform software package for expressed sequences tag (EST) annotation. EST-PAC provides a solution for the administration of EST and protein sequence annotations accessible through a web interface. Three aspects of EST annotation are automated: 1) searching local or remote biological databases for sequence similarities using Blast services, 2) predicting protein coding sequence from EST data and, 3) annotating predicted protein sequences with functional domain predictions. In practice, EST-PAC integrates the BLASTALL suite, EST-Scan2 and HMMER in a relational database system accessible through a simple web interface. EST-PAC also takes advantage of the relational database to allow consistent storage, powerful queries of results and, management of the annotation process. The system allows users to customize annotation strategies and provides an open-source data-management environment for research and education in bioinformatics.

Journal Article↗

PubMed2006

yrGATE: a web-based gene-structure annotation tool for the identification and dissemination of eukaryotic genes.

Your Gene structure Annotation Tool for Eukaryotes (yrGATE) provides an Annotation Tool and Community Utilities for worldwide web-based community genome and gene annotation. Annotators can evaluate gene structure evidence derived from multiple sources to create gene structure annotations. Administrators regulate the acceptance of annotations into published gene sets. yrGATE is designed to facilitate rapid and accurate annotation of emerging genomes as well as to confirm, refine, or correct currently published annotations. yrGATE is highly portable and supports different standard input and output formats. The yrGATE software and usage cases are available at http://www.plantgdb.org/prj/yrGATE.

DNA, Complementary↗

PubMed2006

EGASP: the human ENCODE Genome Annotation Assessment Project.

BACKGROUND: We present the results of EGASP, a community experiment to assess the state-of-the-art in genome annotation within the ENCODE regions, which span 1% of the human genome sequence. The experiment had two major goals: the assessment of the accuracy of computational methods to predict protein coding genes; and the overall assessment of the completeness of the current human genome annotations as represented in the ENCODE regions. For the computational prediction assessment, eighteen groups contributed gene predictions. We evaluated these submissions against each other based on a 'reference set' of annotations generated as part of the GENCODE project. These annotations were not available to the prediction groups prior to the submission deadline, so that their predictions were blind and an external advisory committee could perform a fair assessment. RESULTS: The best methods had at least one gene transcript correctly predicted for close to 70% of the annotated genes. Nevertheless, the multiple transcript accuracy, taking into account alternative splicing, reached only approximately 40% to 50% accuracy. At the coding nucleotide level, the best programs reached an accuracy of 90% in both sensitivity and specificity. Programs relying on mRNA and protein sequences were the most accurate in reproducing the manually curated annotations. Experimental validation shows that only a very small percentage (3.2%) of the selected 221 computationally predicted exons outside of the existing annotation could be verified. CONCLUSION: This is the first such experiment in human DNA, and we have followed the standards established in a similar experiment, GASP1, in Drosophila melanogaster. We believe the results presented here contribute to the value of ongoing large-scale annotation projects and should guide further experimental methods when being scaled up to the entire human genome sequence.

Alternative Splicing↗

PubMed2003

A methodology and implementation for annotating digital images for context-appropriate use in an academic health care environment.

Use of digital medical images has become common over the last several years, coincident with the release of inexpensive, mega-pixel quality digital cameras and the transition to digital radiology operation by hospitals. One problem that clinicians, medical educators, and basic scientists encounter when handling images is the difficulty of using business and graphic arts commercial-off-the-shelf (COTS) software in multicontext authoring and interactive teaching environments. The authors investigated and developed software-supported methodologies to help clinicians, medical educators, and basic scientists become more efficient and effective in their digital imaging environments. The software that the authors developed provides the ability to annotate images based on a multispecialty methodology for annotation and visual knowledge representation. This annotation methodology is designed by consensus, with contributions from the authors and physicians, medical educators, and basic scientists in the Departments of Radiology, Neurobiology and Anatomy, Dermatology, and Ophthalmology at the University of Utah. The annotation methodology functions as a foundation for creating, using, reusing, and extending dynamic annotations in a context-appropriate, interactive digital environment. The annotation methodology supports the authoring process as well as output and presentation mechanisms. The annotation methodology is the foundation for a Windows implementation that allows annotated elements to be represented as structured eXtensible Markup Language and stored separate from the image(s).

Academic Medical Centers↗

PubMed2005

The GATO gene annotation tool for research laboratories.

Large-scale genome projects have generated a rapidly increasing number of DNA sequences. Therefore, development of computational methods to rapidly analyze these sequences is essential for progress in genomic research. Here we present an automatic annotation system for preliminary analysis of DNA sequences. The gene annotation tool (GATO) is a Bioinformatics pipeline designed to facilitate routine functional annotation and easy access to annotated genes. It was designed in view of the frequent need of genomic researchers to access data pertaining to a common set of genes. In the GATO system, annotation is generated by querying some of the Web-accessible resources and the information is stored in a local database, which keeps a record of all previous annotation results. GATO may be accessed from everywhere through the internet or may be run locally if a large number of sequences are going to be annotated. It is implemented in PHP and Perl and may be run on any suitable Web server. Usually, installation and application of annotation systems require experience and are time consuming, but GATO is simple and practical, allowing anyone with basic skills in informatics to access it without any special training. GATO can be downloaded at [http://mariwork.iq.usp.br/gato/]. Minimum computer free space required is 2 MB.

Biomedical Research↗

PubMed2026

Combining Annotation Software to Identify Orthologous Genes (CASIO) Provides a New Dataset of Orthologous Genes for Swallowtail Butterflies.

With the massive increase in genomic resources, it is becoming increasingly popular to analyse thousands of loci across many species. However, many of the available genomes are not annotated, which hinders an efficient search for orthologous protein-coding genes. Here, we aim to develop a semi-automated pipeline and compare four genomic annotation methods (BRAKER2, BUSCO, Miniprot and Scipio). Our results highlight the importance of integrating multiple annotation tools to optimise ortholog detection and improve genomic studies. Each annotation method showed different strengths. BRAKER2 annotated a substantial number of genes. BUSCO, despite limitations inherent to its reference database, identified a higher number of orthologs. Miniprot exhibited notable flexibility in accommodating diverse protein datasets, whereas Scipio successfully recovered a considerable set of genes that were not detected by the other tools. The combination of these tools allowed for more comprehensive ortholog detection. Taking advantage of this pipeline, we developed a comprehensive dataset of orthologous genes for swallowtail butterflies (Lepidoptera: Papilionidae), called Papilionidae_odb, which will facilitate future studies, especially for a non-model group with abundant genomic data and few transcriptomic resources. We tested Papilionidae_odb by inferring a robust phylogenetic framework for Leptocircini using 142 complete genomes, which improved branch support for some phylogenetic relationships, although challenges remained in resolving relationships within certain species groups, likely due to rapid radiations. Our results highlight the complementary nature of the annotation methods and suggest that combining these tools can yield more accurate results in genomic research. This approach was implemented in a Snakemake workflow called CASIO (Combining Annotation Software to Identify Orthologous genes) and can easily be applied to other non-model groups to improve genomic datasets in diverse taxa where transcriptomic resources are still limited.

Animals↗

PubMed2026

ORFannotate: reproducible coding sequence annotation of transcriptome assemblies.

SUMMARY: Accurate annotation of coding sequences and translational features within transcript models is essential for interpreting assembled transcriptomes and their functional potential. Existing open reading frame (ORF) prediction tools typically operate on transcript FASTA files and do not reintegrate coding sequence (CDS) information back into transcript models, limiting their utility in long-read sequencing workflows where GTF/GFF annotations are the primary output. We present ORFannotate, a lightweight, GTF-native Python command-line tool that predicts ORFs from transcript annotations and reinserts precise, exon-aware CDS and UTR features into the original GTF/GFF file. In addition, ORFannotate provides biologically informative translational context by annotating Kozak sequence strength, detecting non-overlapping upstream ORFs (uORFs) with coding probabilities, characterising 5' and 3' untranslated regions (UTRs), and predicting nonsense-mediated decay (NMD) susceptibility. All annotations are consolidated in a transcript-level summary to support downstream analysis. By generating GTF files with accurate CDS annotations, ORFannotate facilitates reproducible analysis of both long- and short-read transcriptomes and integrates seamlessly with visualization tools, genome browsers, and comparative transcript analysis workflows. ORFannotate is fast, scalable and provides a practical solution for transcriptome annotation beyond coding potential prediction alone. AVAILABILITY AND IMPLEMENTATION: ORFannotate is implemented in Python and freely available under the GNU General Public License v3 (GPL-3.0) at: https://github.com/egustavsson/ORFannotate (DOI: https://doi.org/10.5281/zenodo.16812866).

Open Reading Frames↗

PubMed2026

Long-read transcriptomics corrects Trichomonas vaginalis intron annotations and refines transcript-end features.

BACKGROUND: Trichomonas vaginalis causes the most prevalent non-viral sexually transmitted infection worldwide. Despite its large genome (181.5 Mb; 36,310 predicted protein-coding genes in NYU_TvagG3_2), intron annotations remain limited and inconsistently validated. A recent short-read RNA-seq study reported 63 putative active introns, but short reads can misassign splice boundaries and cannot resolve complete transcript structures. METHODS: We integrated Oxford Nanopore direct RNA sequencing (DRS), ONT cDNA long-read sequencing, and Illumina RNA-seq to refine intron annotations, transcript-end features, and UTR boundaries in T. vaginalis. Candidate introns were validated by targeted PCR and Sanger sequencing, and representative splicing events were further assessed using public SRA datasets. RESULTS: Starting from 31 historically annotated introns, motif-guided long-read screening and orthogonal validation identified 17 additional validated introns, increasing the curated set to 48 confirmed introns. Among these 17 events, three were previously unrecognized in the current NYU_TvagG3_2 reference annotation. We also corrected five reported loci, including two false-positive introns, two splice-coordinate misannotations, and one gene-sequence error. DRS further supported transcript termination site mapping, UAAA polyadenylation-signal profiling relative to poly(A) addition sites, and single-molecule poly(A)-tail estimation. StringTie mixed-mode assemblies provided updated UTR boundaries for intron-bearing transcripts and transcripts without curated introns. CONCLUSIONS: This study provides a rigorously validated, long-read-refined resource of intron annotations, UTR boundaries, and UAAA-guided transcript-end features for T. vaginalis, together with a reproducible workflow for non-model protists. These refinements improve the current reference annotation and support future studies of functional genomics, parasite biology, pathogenesis, and diagnostic development.

Trichomonas vaginalis↗

PubMed2004

Semia: semi-automatic interactive graphic editing tool to annotate ambulatory ECG records.

We designed and developed a special purpose interactive graphic editing tool semi-automatic (Semia) to annotate transient ischaemic ST segment episodes and other non-ischaemic ST segment events in 24h ambulatory electrocardiogram (ECG) records. The tool allows representation and viewing of the data, interaction with the data globally and locally at different resolutions, examining data at any point, manual adjustment of heart-beat fiducial points, and manual and automatic editing of annotations. Efficient and fast display of ambulatory ECG signal waveforms, display of diagnostic and morphology feature-vector time-series, dynamic interface controls, and automated procedures to help annotate, made the tool efficient, user friendly and usable. Human expert annotators used the Semia tool to successfully annotate the Long-Term ST database (LTST DB), a result of a multinational effort. The tool supported paperless editing of annotations at dislocated geographical sites. We present design, characteristic "look and feel", functionality, and development of Semia annotating tool.

Ambulatory Care Information Systems↗

PubMed2005

Automatic annotation of protein function.

The annotation of protein function at genomic scale is essential for day-to-day work in biology and for any systematic approach to the modeling of biological systems. Currently, functional annotation is essentially based on the expansion of the relatively small number of experimentally determined functions to large collections of proteins. The task of systematic annotation faces formidable practical problems related to the accuracy of the input experimental information, the reliability of current systems for transferring information between related sequences, and the reproducibility of the links between database information and the original experiments reported in publications. These technical difficulties merely lie on the surface of the deeper problem of the evolution of protein function in the context of protein sequences and structures. Given the mixture of technical and scientific challenges, it is not surprising that errors are introduced, and expanded, in database annotations. In this situation, a more realistic option is the development of a reliability index for database annotations, instead of depending exclusively on efforts to correct databases. Several groups have attempted to compare the database annotations of similar proteins, which constitutes the first steps toward the calibration of the relationship between sequence and annotation space.

Artificial Intelligence↗

PubMed2005

Community-based gene structure annotation.

Uncertainty and inconsistency of gene structure annotation remain limitations on research in the genome era, frustrating both biologists and bioinformaticians, who have to sort out annotation errors for their genes of interest or to generate trustworthy datasets for algorithmic development. It is unrealistic to hope for better software solutions in the near future that would solve all the problems. The issue is all the more urgent with more species being sequenced and analyzed by comparative genomics - erroneous annotations could easily propagate, whereas correct annotations in one species will greatly facilitate annotation of novel genomes. We propose a dynamic, economically feasible solution to the annotation predicament: broad-based, web-technology-enabled community annotation, a prototype of which is now in use for Arabidopsis.

Arabidopsis↗

PubMed2003

Automated annotation of microbial proteomes in SWISS-PROT.

Large-scale sequencing of prokaryotic genomes demands the automation of certain annotation tasks currently manually performed in the production of the SWISS-PROT protein knowledgebase. The HAMAP project, or 'High-quality Automated and Manual Annotation of microbial Proteomes', aims to integrate manual and automatic annotation methods in order to enhance the speed of the curation process while preserving the quality of the database annotation. Automatic annotation is only applied to entries that belong to manually defined orthologous families and to entries with no identifiable similarities (ORFans). Many checks are enforced in order to prevent the propagation of wrong annotation and to spot problematic cases, which are channelled to manual curation. The results of this annotation are integrated in SWISS-PROT, and a website is provided at http://www.expasy.org/sprot/hamap/.

Amino Acid Sequence↗

PubMed2001

Electroanatomical Mapping (CARTO) of ectopic atrial tachycardia: impact of bipolar and unipolar local electrogram annotation for localization the focal origin.

UNLABELLED: Electroanatomical Mapping (CARTO) allows a tridimensional localization of ectopic atrial tachycardia (EAT). No standardized recommendation exists for annotation the local activation time in EAT using this new technology. In the present study bipolar local electrogram were used for CARTO guided RF ablation of EAT. In comparison the same maps were retrospectively analyzed by annotation the unipolar local electrogram. METHODS: In 15 consecutive patients (6m, 51+/-14 y) with EAT CARTO mapping was guided by annotation the earliest onset of the bipolar local electrogram. Following successful RF ablation the obtained EAT maps were subsequently evaluated by annotation of the earliest steepest negative intrinsic deflection of the unipolar local electrogram. Both CARTO maps were compared with regard to the region of focal EAT origin. RESULTS: RF ablation of all 15 EAT foci guided by annotation the bipolar local electrogram with CARTO was successful with a median of 3 [1-18] pulses and a median fluoroscopy time of 10 min [4-25]. All but one focus was located in the right atrium: posterior to posteroinferior region of the terminal crest in 6, septal region in 5, anterior superior region in 3 cases. One left sided EAT was located at the septum. The bipolar CARTO map demonstrated a "small territory" location of earliest activation (extension of the focus < or =0.4 cm(2)) in 14 out of 15 patients. In a single patient the bipolar map showed several sites of earliest local activation (extension >0.4 cm(2)). On the other side the retrospectively achieved unipolar maps demonstrated an extended region of earliest local activation in 6 out of 15 patients (>0.4 cm(2)). CONCLUSIONS: CARTO maps of EAT by annotation the earliest onset of the bipolar local electrogram provide an efficacious guide for location the focal origin. Extended regions of earliest local activation in EAT might be rather determined by annotation the unipolar in comparison to the bipolar local electrogram.

Adult↗

PubMed2006

Towards multidimensional genome annotation.

Our information about the gene content of organisms continues to grow as more genomes are sequenced and gene products are characterized. Sequence-based annotation efforts have led to a list of cellular components, which can be thought of as a one-dimensional annotation. With growing information about component interactions, facilitated by the advancement of various high-throughput technologies, systemic, or two-dimensional, annotations can be generated. Knowledge about the physical arrangement of chromosomes will lead to a three-dimensional spatial annotation of the genome and a fourth dimension of annotation will arise from the study of changes in genome sequences that occur during adaptive evolution. Here we discuss all four levels of genome annotation, with specific emphasis on two-dimensional annotation methods.

Archaeal Proteins↗

PubMedDate not supplied

Evaluation of human-readable annotation in biomolecular sequence databases with biological rule libraries.

MOTIVATION: Computer-based selection of entries from sequence databases with respect to a related functional description, e.g. with respect to a common cellular localization or contributing to the same phenotypic function, is a difficult task. Automatic semantic analysis of annotations is not only hampered by incomplete functional assignments. A major problem is that annotations are written in a rich, non-formalized language and are meant for reading by a human expert. This person can extract from the text considerably more information than is immediately apparent due to his extended biological background knowledge and logical reasoning. APPROACH: A technique of automated annotation evaluation based on a combination of lexical analysis and the usage of biological rule libraries has been developed. The proposed algorithm generates new functional descriptors from the annotation of a given entry using the semantic units of the annotation as prepositions for implications executed in accordance with the rule library. RESULTS: The prototype of a software system, the Meta_A(nnotator) program, is described and the results of its application to sequence attribute assignment and sequence selection problems, such as cellular localization and sequence domain annotation of SWISS-PROT entries, are presented. The current software version assigns useful subcellular localization qualifiers to approximately 88% of all SWISS-PROT entries. As shown by demonstrative examples, the combination of sequence and annotation analysis is a powerful approach for the detection of mutual annotation/sequence inconsistencies. AVAILABILITY: Results for the cellular localization assignment can be viewed at the URL http://www.bork. embl-heidelberg.de/CELL_LOC/CELL_LOC.html.

Algorithms↗

PubMed2005

Automated genome annotation and pathway identification using the KEGG Orthology (KO) as a controlled vocabulary.

MOTIVATION: High-throughput technologies such as DNA sequencing and microarrays have created the need for automated annotation of large sets of genes, including whole genomes, and automated identification of pathways. Ontologies, such as the popular Gene Ontology (GO), provide a common controlled vocabulary for these types of automated analysis. Yet, while GO offers tremendous value, it also has certain limitations such as the lack of direct association with pathways. RESULTS: We demonstrated the use of the KEGG Orthology (KO), part of the KEGG suite of resources, as an alternative controlled vocabulary for automated annotation and pathway identification. We developed a KO-Based Annotation System (KOBAS) that can automatically annotate a set of sequences with KO terms and identify both the most frequent and the statistically significantly enriched pathways. Results from both whole genome and microarray gene cluster annotations with KOBAS are comparable and complementary to known annotations. KOBAS is a freely available stand-alone Python program that can contribute significantly to genome annotation and microarray analysis.

Artificial Intelligence↗

PubMed2006

Using hidden Markov models and observed evolution to annotate viral genomes.

MOTIVATION: ssRNA (single stranded) viral genomes are generally constrained in length and utilize overlapping reading frames to maximally exploit the coding potential within the genome length restrictions. This overlapping coding phenomenon leads to complex evolutionary constraints operating on the genome. In regions which code for more than one protein, silent mutations in one reading frame generally have a protein coding effect in another. To maximize coding flexibility in all reading frames, overlapping regions are often compositionally biased towards amino acids which are 6-fold degenerate with respect to the 64 codon alphabet. Previous methodologies have used this fact in an ad hoc manner to look for overlapping genes by motif matching. In this paper differentiated nucleotide compositional patterns in overlapping regions are incorporated into a probabilistic hidden Markov model (HMM) framework which is used to annotate ssRNA viral genomes. This work focuses on single sequence annotation and applies an HMM framework to ssRNA viral annotation. A description of how the HMM is parameterized, whilst annotating within a missing data framework is given. A Phylogenetic HMM (Phylo-HMM) extension, as applied to 14 aligned HIV2 sequences is also presented. This evolutionary extension serves as an illustration of the potential of the Phylo-HMM framework for ssRNA viral genomic annotation. RESULTS: The single sequence annotation procedure (SSA) is applied to 14 different strains of the HIV2 virus. Further results on alternative ssRNA viral genomes are presented to illustrate more generally the performance of the method. The results of the SSA method are encouraging however there is still room for improvement, and since there is overwhelming evidence to indicate that comparative methods can improve coding sequence (CDS) annotation, the SSA method is extended to a Phylo-HMM to incorporate evolutionary information. The Phylo-HMM extension is applied to the same set of 14 HIV2 sequences which are pre-aligned. The performance improvement that results from including the evolutionary information in the analysis is illustrated.

Algorithms↗

PubMed2006

Annotating proteins by mining protein interaction networks.

MOTIVATION: In general, most accurate gene/protein annotations are provided by curators. Despite having lesser evidence strengths, it is inevitable to use computational methods for fast and a priori discovery of protein function annotations. This paper considers the problem of assigning Gene Ontology (GO) annotations to partially annotated or newly discovered proteins. RESULTS: We present a data mining technique that computes the probabilistic relationships between GO annotations of proteins on protein-protein interaction data, and assigns highly correlated GO terms of annotated proteins to non-annotated proteins in the target set. In comparison with other techniques, probabilistic suffix tree and correlation mining techniques produce the highest prediction accuracy of 81% precision with the recall at 45%. AVAILABILITY: Code is available upon request. Results and used materials are available online at http://kirac.case.edu/PROTAN.

Amino Acid Sequence↗