Biomedical subjects

Yanbin Yin

Publications and source records attributed to Yanbin Yin.

4 recordsLinked to original sources

PubMed2025

A chromosome-level genome assembly of Coffea arabica L. var. 'Kona Typica'.

Coffea arabica L. var. 'Kona Typica' is renowned for its premium cup quality, but its vulnerability to pests and diseases limits production. To accelerate cultivar improvement, we generated a chromosome-level genome assembly of 'Kona Typica' using PacBio HiFi sequencing and Hi-C scaffolding technology. The final assembly spans 1.13 Gb, with a scaffold N50 of 50.50 Mb, organized into 22 chromosomes. BUSCO assessment indicated a high completeness at 99.1%. We annotated 65,458 protein-coding genes and identified 1,073,545 interspersed repeats, accounting for 65.16% of the genome. Analysis of transposon insertion ages revealed that most long terminal repeat retrotransposons proliferated after the polyploidization event. This high-quality genome assembly of 'Kona Typica' provides a valuable resource for exploring coffee genomic evolution and genetic mechanisms of complex traits, facilitating genomics studies and the development of improved coffee cultivars with enhanced disease resistance and quality traits.

Coffea↗

PubMed2005

SPD--a web-based secreted protein database.

With the improved secreted protein prediction approach and comprehensive data sources, including Swiss-Prot, TrEMBL, RefSeq, Ensembl and CBI-Gene, we have constructed secretomes of human, mouse and rat, with a total of 18 152 secreted proteins. All the entries are ranked according to the prediction confidence. They were further annotated via a proteome annotation pipeline that we developed. We also set up a secreted protein classification pipeline and classified our predicted secreted proteins into different functional categories. To make the dataset more convincing and comprehensive, nine reference datasets are also integrated, such as the secreted proteins from the Gene Ontology Annotation (GOA) system at the European Bioinformatics Institute, and the vertebrate secreted proteins from Swiss-Prot. All these entries were grouped via a TribeMCL based clustering pipeline. We have constructed a web-based secreted protein database, which has been publicly available at http://spd.cbi.pku.edu.cn. Users can browse the database via a GO assignment or chromosomal-location-based interface. Moreover, text query and sequence similarity search are also provided, and the sequence and annotation data can be downloaded freely from the SPD website.

Animals↗

PubMed2003

PCAS--a precomputed proteome annotation database resource.

BACKGROUND: Many model proteomes or "complete" sets of proteins of given organisms are now publicly available. Much effort has been invested in computational annotation of those "draft" proteomes. Motif or domain based algorithms play a pivotal role in functional classification of proteins. Employing most available computational algorithms, mainly motif or domain recognition algorithms, we set up to develop an online proteome annotation system with integrated proteome annotation data to complement existing resources. RESULTS: We report here the development of PCAS (ProteinCentric Annotation System) as an online resource of pre-computed proteome annotation data. We applied most available motif or domain databases and their analysis methods, including hmmpfam search of HMMs in Pfam, SMART and TIGRFAM, RPS-PSIBLAST search of PSSMs in CDD, pfscan of PROSITE patterns and profiles, as well as PSI-BLAST search of SUPERFAMILY PSSMs. In addition, signal peptide and TM are predicted using SignalP and TMHMM respectively. We mapped SUPERFAMILY and COGs to InterPro, so the motif or domain databases are integrated through InterPro. PCAS displays table summaries of pre-computed data and a graphical presentation of motifs or domains relative to the protein. As of now, PCAS contains human IPI, mouse IPI, and rat IPI, A. thaliana, C. elegans, D. melanogaster, S. cerevisiae, and S. pombe proteome.PCAS is available at http://pak.cbi.pku.edu.cn/proteome/gca.php CONCLUSION: PCAS gives better annotation coverage for model proteomes by employing a wider collection of available algorithms. Besides presenting the most confident annotation data, PCAS also allows customized query so users can inspect statistically less significant boundary information as well. Therefore, besides providing general annotation information, PCAS could be used as a discovery platform. We plan to update PCAS twice a year. We will upgrade PCAS when new proteome annotation algorithms identified.

Algorithms↗

PubMed2003

PepPat, a pattern-based oligopeptide homology search method and the identification of a novel tachykinin-like peptide.

UNLABELLED: PepPat, a hybrid method that combines pattern matching with similarity scoring, is described. We also report PepPat's application in the identification of a novel tachykinin-like peptide. PepPat takes as input a query peptide and a user-specified regular expression pattern within the peptide. It first performs a database pattern match and then ranks candidates on the basis of their similarity to the query peptide. PepPat calculates similarity over the pattern spanning region, enhancing PepPat's sensitivity for short query peptides. PepPat can also search for a user-specified number of occurrences of a repeated pattern within the target sequence. We illustrate PepPat's application in short peptide ligand mining. As a validation example, we report the identification of a novel tachykinin-like peptide, C14TKL-1, and show it is an NK1 (neuokinin receptor 1) agonist whose message is widely expressed in human periphery. AVAILABILITY: PepPat is offered online at: http://peppat.cbi.pku.edu.cn.

Algorithms↗