Most cited papers from Bioinformatics Solutions (Canada)
What are the most cited papers from Bioinformatics Solutions (Canada)?
The most cited paper from Bioinformatics Solutions (Canada) is "Initial sequencing and comparative analysis of the mouse genome" (Asif T. Chinwalla et al., 2002), with 7,343 citations. Next come "PEAKS: powerful software for peptide de novo sequencing by tandem mass spectrometry" (1,409) and "PEAKS DB: De Novo Sequencing Assisted Database Search for Sensitive and Accurate Peptide Identification" (1,132).
Showing 50 of 59 papers. Every paper with more than 8 citations is listed.
| # | Paper | ||
|---|---|---|---|
| 1 | Initial sequencing and comparative analysis of the mouse genome Asif T. Chinwalla et al. · Nature | Dec 2002 | 7,343 |
| 2 | PEAKS: powerful software for peptide de novo sequencing by tandem mass spectrometry Bin Ma, Kaizhong Zhang, Christopher Hendrie et al. · Rapid Communications in Mass Spectrometry | 19 Sep 2003 | 1,409 |
| 3 | PEAKS DB: De Novo Sequencing Assisted Database Search for Sensitive and Accurate Peptide Identification Jing Zhang, Lei Xin, Baozhen Shan et al. · Molecular & Cellular Proteomics | 21 Dec 2011 | 1,132 |
| 4 | PatternHunter: faster and more sensitive homology search Bin Ma, John Tromp, Ming Li · Bioinformatics | Mar 2002 | 865 |
| 5 | An information-based sequence distance and its application to whole mitochondrial genome phylogeny Ming Li, Jonathan H. Badger, Xin Chen et al. · Bioinformatics | Feb 2001 | 543 |
| 6 | De novo peptide sequencing by deep learning Ngoc Hieu Tran, Xianglilan Zhang, Lei Xin et al. · Proceedings of the National Academy of Sciences | 18 Jul 2017 | 485 |
| 7 | Deep learning enables de novo peptide sequencing from data-independent-acquisition mass spectrometry Ngoc Hieu Tran, Rui Qiao, Lei Xin et al. · Nature Methods | 7 Dec 2018 | 395 |
| 8 | PATTERNHUNTER II: HIGHLY SENSITIVE AND FAST HOMOLOGY SEARCH MING LI, BIN MA, Derek Kisman et al. · Journal of Bioinformatics and Computational Biology | Sep 2004 | 231 |
| 9 | DNACompress: fast and effective DNA sequence compression Xin Chen, Ming Li, Bin Ma et al. · Bioinformatics | Dec 2002 | 211 |
| 10 | PeaksPTM: Mass Spectrometry-Based Identification of Peptides with Unspecified Modifications Han Xi, Lin He, Lei Xin et al. · Journal of Proteome Research | 24 May 2011 | 183 |
| 11 | Complete De Novo Assembly of Monoclonal Antibody Sequences Ngoc Hieu Tran, M. Ziaur Rahman, Lin He et al. · Scientific Reports | 26 Aug 2016 | 173 |
| 12 | A streamlined platform for analyzing tera-scale DDA and DIA mass spectrometry data enables highly sensitive immunopeptidomics Lei Xin, Rui Qiao, Xin Chen et al. · Nature Communications | 7 Jun 2022 | 109 |
| 13 | Mondo: Unifying diseases for the world, by the world Nicole Vasilevsky et al. · medRxiv | 16 Apr 2022 | 104 |
| 14 | Computationally instrument-resolution-independent de novo peptide sequencing for high-resolution devices Rui Qiao, Ngoc Hieu Tran, Lei Xin et al. · Nature Machine Intelligence | 18 Mar 2021 | 103 |
| 15 | Expanding Proteome Coverage with CHarge Ordered Parallel Ion aNalysis (CHOPIN) Combined with Broad Specificity Proteolysis Simon A. Davis, Philip D. Charles, Lin He et al. · Journal of Proteome Research | 6 Feb 2017 | 100 |
| 16 | The similarity metric Ming Li, Xin Chen, Xin Yan Li et al. · UvA-DARE (University of Amsterdam) | 12 Jan 2003 | 98 |
| 17 | Chemoproteomic profiling and discovery of protein electrophiles in human cells Megan L. Matthews, Lin He, Benjamin D. Horning et al. · Nature Chemistry | 31 Oct 2016 | 93 |
| 18 | A draft genome sequence of the elusive giant squid, Architeuthis dux Rute R. da Fonseca et al. · GigaScience | 2020 | 92 |
| 19 | Climate change, non‐indigenous species and shipping: assessing the risk of species introduction to a high‐ A rctic archipelago Chris Ware, Jørgen Berge, Jan Henry Sundet et al. · Diversity and Distributions | 12 Aug 2013 | 89 |
| 20 | GlycoMaster DB: Software To Assist the Automated Identification of N-Linked Glycopeptides by Tandem Mass Spectrometry He Lin, Lei Xin, Baozhen Shan et al. · Journal of Proteome Research | 12 Aug 2014 | 87 |
| 21 | DeepIso: A Deep Learning Model for Peptide Feature Detection from LC-MS map Fatema Tuz Zohora, M. Ziaur Rahman, Ngoc Hieu Tran et al. · Scientific Reports | 20 Nov 2019 | 85 |
| 22 | A network of RNA-binding proteins controls translation efficiency to activate anaerobic metabolism J.J.David Ho, Nathan C. Balukoff, Phaedra R. Theodoridis et al. · Nature Communications | 29 May 2020 | 67 |
| 23 | Glycopeptide database search and de novo sequencing with PEAKS GlycanFinder enable highly sensitive glycoproteomics Weiping Sun, Qianqiu Zhang, Xiyue Zhang et al. · Nature Communications | 8 Jul 2023 | 60 |
| 24 | Better score function for peptide identification with ETD MS/MS spectra Xiaowen Liu, Baozhen Shan, Lei Xin et al. · BMC Bioinformatics | 2010 | 48 |
| 25 | A randomized phase 2b trial examined the effects of the glucagon-like peptide-1 and glucagon receptor agonist cotadutide on kidney outcomes in patients with diabetic kidney disease Viknesh Selvarajah et al. · Kidney International | 30 Aug 2024 | 43 |
| 26 | Grand challenges in bioinformatics education and training Esra Büşra Işık et al. · Nature Biotechnology | Aug 2023 | 43 |
| 27 | An effective algorithm for peptide de novo sequencing from MS/MS spectra Bin Ma, Kaizhong Zhang, Chengzhi Liang · Journal of Computer and System Sciences | 8 Feb 2005 | 43 |
| 28 | Personalized deep learning of individual immunopeptidomes to identify neoantigens for cancer vaccines Ngoc Hieu Tran, Rui Qiao, Lei Xin et al. · Nature Machine Intelligence | 16 Nov 2020 | 42 |
| 29 | Digestion-Free Analysis of Peptides from 30-year-old Formalin-Fixed, Paraffin-Embedded Tissue by Mass Spectrometry Imaging Martin R. L. Paine, Shane R. Ellis, Dan Maloney et al. · Analytical Chemistry | 5 Jul 2018 | 42 |
| 30 | Automated protein (re)sequencing with MS/MS and a homologous database yields almost full coverage and accuracy Xiaowen Liu, Yonghua Han, Denis Yuen et al. · Bioinformatics | 17 Jun 2009 | 40 |
| 31 | Mitigating the missing-fragmentation problem in de novo peptide sequencing with a two-stage graph-based deep learning model Zeping Mao, Ruixue Zhang, Lei Xin et al. · Nature Machine Intelligence | 19 Oct 2023 | 38 |
| 32 | Forewing pigmentation predicts migration distance in wild-caught migratory monarch butterflies Daniel Hanley, Nathan G. Miller, D. T. Tyler Flockhart et al. · Behavioral Ecology | 2013 | 34 |
| 33 | The WRKY Transcription Factor Genes in Eggplant (Solanum melongena L.) and Turkey Berry (Solanum torvum Sw.) Xu Yang, Cao Deng, Yu Zhang et al. · International Journal of Molecular Sciences | 7 Apr 2015 | 32 |
| 34 | Proteomics reveal cap-dependent translation inhibitors remodel the translation machinery and translatome J.J.David Ho, Tyler Andrew Cunningham, Paola Manara et al. · Cell Reports | Oct 2021 | 30 |
| 35 | tPatternHunter: gapped, fast and sensitive translated homology search Derek Kisman, Ming Li, Bin Ma et al. · Bioinformatics | 16 Sep 2004 | 28 |
| 36 | Covalent Immune Proximity-Induction Strategy Using SuFEx-Engineered Bifunctional Viral Peptides Harrison M. McCann, Benjamin P. M. Lake, Kyle S. Hoffman et al. · ACS Chemical Biology | 6 May 2022 | 27 |
| 37 | Through the eye of an electrospray needle: mass spectrometric identification of the major peptides and proteins in the milk of the one‐humped camel (Camelus dromedarius) Abdulqader A. Alhaider, Abdel Galil Abdelgader, Abdullah Arif Turjoman et al. · Journal of Mass Spectrometry | 18 Jun 2013 | 27 |
| 38 | A Disaggregated Packet Processing Architecture for Network Function Virtualization Shihabur Rahman Chowdhury, Anthony Anthony, Haibo Bian et al. · IEEE Journal on Selected Areas in Communications | 8 Apr 2020 | 25 |
| 39 | Analysis of iTRAQ data using Mascot and Peaks quantification algorithms Carla M. R. Lacerda, Lei Xin, Iain Rogers et al. · Briefings in Functional Genomics and Proteomics | 12 Feb 2008 | 24 |
| 40 | An Effective Algorithm for the Peptide De Novo Sequencing from MS/MS Spectrum Bin Ma, Kaizhong Zhang, Chengzhi Liang · Lecture notes in computer science | 2003 | 23 |
| 41 | ZOOM Lite: next-generation sequencing data mapping and visualization software Zhiwu S. Zhang, He Lin, Bin Ma · Nucleic Acids Research | 8 Jun 2010 | 19 |
| 42 | Computational proteomics pitfalls and challenges: HavanaBioinfo 2012 Workshop report Yasset Pérez‐Riverol et al. · Journal of Proteomics | 29 Jan 2013 | 19 |
| 43 | A three-dimensional groundwater flow model of the Waterloo Moraine for water resource management Patricia A. Meyer, Martinus Brouwers, Paul J. Martin · Canadian Water Resources Journal / Revue canadienne des ressources hydriques | 3 Apr 2014 | 19 |
| 44 | Bacterial translation machinery for deliberate mistranslation of the genetic code Oscar Vargas‐Rodriguez, Ahmed H. Badran, Kyle S. Hoffman et al. · Proceedings of the National Academy of Sciences | 19 Aug 2021 | 18 |
| 45 | Proteomic and functional mapping of cardiac NaV1.5 channel phosphorylation sites Maxime Lorenzini, Sophie Burel, Adrien Lesage et al. · The Journal of General Physiology | 13 Nov 2020 | 18 |
| 46 | DISGENET: Accelerating Data-Driven Discovery in Disease Genomics and Therapeutic Development Janet Piñero, Javier Corvi, Natalia Rykova et al. · bioRxiv (Cold Spring Harbor Laboratory) | 5 Jan 2026 | 15 |
| 47 | A translational program that suppresses metabolism to shield the genome Nathan C. Balukoff, J.J.David Ho, Phaedra R. Theodoridis et al. · Nature Communications | 13 Nov 2020 | 15 |
| 48 | Insights from four decades of model development on the Waterloo Moraine: A review Emil O. Frind, John W. Molson, Marcelo R. Sousa et al. · Canadian Water Resources Journal / Revue canadienne des ressources hydriques | 3 Apr 2014 | 15 |
| 49 | Mistranslating the genetic code with leucine in yeast and mammalian cells Josephine Davey-Young, Farah Hasan, Rasangi Tennakoon et al. · RNA Biology | 17 Apr 2024 | 14 |
| 50 | Mistranslation of the genetic code by a new family of bacterial transfer RNAs Dominik B. Schuntermann, Jonathan T. Fischer, Jonmatthew Bile et al. · Journal of Biological Chemistry | 22 May 2023 | 14 |
Citations are OpenAlex's own counts, from its 2026-09-23 snapshot, so the ranking can differ from Google Scholar or Web of Science. A paper is listed for an institution when any of its authors gave it as an affiliation; retracted papers and papers whose citation count cannot be traced to citing works are left out, and a preprint and the article it became are shown once. Release dates are OpenAlex's: where a source gave only a month or a year, that is what is shown. How the lists are chosen.