Homology search
12 methods · 2001–2025
Homology search: De novo sequences, errors and all, used as the query in an error-tolerant search against known proteins, so a protein that is in no database can still be identified through its relatives.
De novo sequences, errors and all, used as the query in an error-tolerant search against known proteins, so a protein that is in no database can still be identified through its relatives.
The earliest of its 12 methods is MS BLAST (2001); 11 more have followed.
| Methods | 12 |
| Papers describing them | 19 |
| Authors | 75 |
| Active | 2001-05-01 to 2025-06-02 |
| Kinds | adjacent (9), algorithm (2), post-processor |
| Acquisition | DDA (11), DIA |
Methods (12)
Oldest first, by the paper that describes each one.
- MS BLAST (2001): Homology search of error-tolerant de novo sequences against a protein database, introduced for charting the proteomes of organisms with unsequenced genomes and later used to validate borderline identifications.
- Homology-tolerant search parameters (MS-Homology) (2004): Optimises how many de novo derived peptide sequences and what mismatch level to submit to MS-Homology for identifying proteins absent from the database, and compares the result with Mascot.
- SPIDER (2005): Protein identification from sequence tags while accounting for de novo sequencing error.
- Genomic Peptide Finder (2006): Aligns de novo sequenced peptides directly to a genome, tolerating sequencing errors and introns, to provide proteogenomic evidence for gene annotation.
- Layered sequence-similarity proteomics (2007): Identifies proteins in organisms with unsequenced genomes by layering the search: a stringent database search first, then automated de novo sequencing of what it leaves behind, then sequence-similarity searching of those de novo reads against related species.
- PepTiger (2007): Matches error-prone de novo sequences to database peptides with approximate string matching and a combined mass and spectrum score.
- Unsequenced-organism de novo workflow (2007): Combines spectrum quality filtering, multiple de novo sequencing tools and error-tolerant BLAST to identify proteins from organisms without a genome.
- Champs (2009): Sequences a complete novel protein by de novo sequencing its peptides and then assembling them against a HOMOLOGOUS database rather than an exact one, reaching near-full coverage and accuracy where neither approach alone would.
- PepExplorer (2014): Aligns de novo peptide sequences from several tools against a target-decoy database and uses a neural network to report homologous proteins at a controlled FDR.
- SPIDER-TMS (2016): A software package automating de novo sequencing by matching spectra to a randomized sequence database and transcriptome data for protein identification.
- HyPep (2023): Open-source tool that aligns PEAKS de novo sequences against neuropeptide databases with sequence-homology scoring to identify known and discover new neuropeptides.
- DIAVariant (2025): Identifies peptide sequence variants directly from DIA spectra by de novo sequencing-assisted homology search, with rigorous FDR control, so variant peptides outside the database can be found without a DDA library.
Papers describing them (19)
- Charting the Proteomes of Organisms with Unsequenced Genomes by MALDI-Quadrupole Time-of-Flight Mass Spectrometry and BLAST Homology Searching (2001, Analytical Chemistry, peer-reviewed)
- The Power and the Limitations of Cross-Species Protein Identification by Mass Spectrometry-driven Sequence Similarity Searches (2004, Molecular & Cellular Proteomics, peer-reviewed)
- Defining parameters for homology-tolerant database searching (2004, PubMed, peer-reviewed)
- SPIDER: software for protein identification from sequence tags with de novo sequencing error (2005, Journal of Bioinformatics and Computational Biology, peer-reviewed)
- Rapid Validation of Protein Identifications with the Borderline Statistical Confidence via De Novo Sequencing and MS BLAST Searches (2006, Journal of Proteome Research, peer-reviewed)
- Mass spectrometric genomic data mining: Novel insights into bioenergetic pathways in Chlamydomonas reinhardtii (2006, PROTEOMICS, peer-reviewed)
- Sequence similarity‐driven proteomics in organisms with unknown genomes by LC‐MS/MS and automated de novo sequencing (2007, PROTEOMICS, peer-reviewed)
- A robust algorithm for identification of proteins in a database (2007, Moscow University Computational Mathematics and Cybernetics, peer-reviewed)
- A workflow to increase the detection rate of proteins from unsequenced organisms in high‐throughput proteomics experiments (2007, PROTEOMICS, peer-reviewed)
- PepTiger: Search Engine for Error-Tolerant Protein Identification from de Novo Sequences (2007, The Open Spectroscopy Journal, peer-reviewed)
- Automated protein (re)sequencing with MS/MS and a homologous database yields almost full coverage and accuracy (2009, Bioinformatics, peer-reviewed)
- SPIDER: Reconstructive Protein Homology Search with De Novo Sequencing Tags (2011, thesis)
- Concerted action of the new Genomic Peptide Finder and AUGUSTUS allows for automated proteogenomic annotation of the Chlamydomonas reinhardtii genome (2011, PROTEOMICS, peer-reviewed)
- Integrating de novo Sequencing and Database Search for Monoclonal Antibody Sequencing (2013, Europe PMC (PubMed Central), abstract)
- PepExplorer: A Similarity-driven Tool for Analyzing de Novo Sequencing Results (2014, Molecular & Cellular Proteomics, peer-reviewed)
- Using PepExplorer to Filter and Organize De Novo Peptide Sequencing Results (2015, Current Protocols in Bioinformatics, peer-reviewed)
- Sequence Protein Identification by Randomized Sequence Database and Transcriptome Mass Spectrometry (SPIDER-TMS): From Manual to Automatic Application of a ‘ de Novo Sequencing’ Approach (2016, European Journal of Mass Spectrometry, peer-reviewed)
- HyPep: An Open-Source Software for Identification and Discovery of Neuropeptides Using Sequence Homology Search (2023, Journal of Proteome Research, peer-reviewed)
- De Novo sequencing-assisted homology search for DIA data analysis enables low abundance peptide variants discovery (2025, bioRxiv, preprint)