Article
Biochemical Research Methods
Yannek Nowatzky, Philipp Benner, Knut Reinert, Thilo Muth
Summary: This study demonstrates a workflow that utilizes Prosit for spectral library predictions and implements an indexing and search algorithm, Mistle, to efficiently identify experimental mass spectra within the library. Mistle outperforms other spectral library search engines in terms of accuracy, run time, and memory usage.
Article
Multidisciplinary Sciences
Jen-Hung Wang, Wai-Kok Choong, Ching-Tai Chen, Ting-Yi Sung
Summary: This article introduces a spectral library search tool called Calibr for spectrum-centric DIA data analysis. Calibr improves the number of spectrum-spectrum matches and peptides compared to traditional preprocessing methods. When compared to DDA and MassIVE spectral libraries, Calibr also demonstrates higher sensitivity.
SCIENTIFIC REPORTS
(2022)
Article
Biochemical Research Methods
Sebastian Dorl, Stephan Winkler, Karl Mechtler, Viktoria Dorfer
Summary: Spectral library search enables more sensitive peptide identification in tandem mass spectrometry experiments, but suffers from limited availability of high-quality libraries and the difficulty of creating decoy spectra for result validation. MS Ana is a new spectral library search engine that addresses these issues by allowing the use of curated or predicted libraries and providing robust false discovery control through its own decoy library generation algorithm. In benchmark tests, MS Ana outperformed database search, achieving 36% more spectrum matches and 4% more proteins identified in single-shot human cell-line data. The quality of result validation was demonstrated through tests on synthetic peptide pools, and the importance of library selection was highlighted by comparing the performance of different publicly available human spectral libraries.
JOURNAL OF PROTEOME RESEARCH
(2023)
Article
Biochemical Research Methods
Genet Abay Shiferaw, Ralf Gabriels, Robbin Bouwmeester, Tim Van den Bossche, Elien Vandermarliere, Lennart Martens, Pieter-Jan Volders
Summary: Maintaining high sensitivity while limiting false positives in peptide identification from mass spectrometry data is a key challenge. This study investigates the effects of integrating the machine learning-based postprocessor Percolator into the spectral library searching tool COSS.
JOURNAL OF PROTEOME RESEARCH
(2022)
Article
Biochemical Research Methods
Nicolai B. Palstrom, Amanda J. Campbell, Caroline A. Lindegaard, Samir Cakar, Rune Matthiesen, Hans C. Beck
Summary: This study developed a TMTpro-specific spectral library for improved protein identification in human plasma proteomics. The spectral library showed improved protein identification compared to conventional sequence database searching, providing a resource for future plasma proteomics research.
Article
Computer Science, Artificial Intelligence
Ying Li, Mingzhou Chen, Jiazhen Huo
Summary: This paper aims to solve the large-scale heterogeneous container loading problem with a hybrid adaptive large neighborhood search algorithm. Computational experiments show that the proposed algorithm outperforms other algorithms for the HCLP.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Automation & Control Systems
Ruoqiu Zhang, Zhaocong Shang, Siqian Lu, Nan Jia, Xin Jiang, Zhengyu Pu, Yiping Du, Yun Hu
Summary: A new method named SPCV is proposed in this study to advance Raman spectral library search by partitioning spectra based on Voigt function and correcting inconsistent peak intensity. The results demonstrate that SPCV can significantly increase Pearson's correlation coefficient values and improve the performance of spectral matching. Furthermore, SPCV outperforms other indexes in terms of matching accuracy rate, making it a promising candidate for enhancing library-based Raman spectral matching.
CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS
(2021)
Article
Computer Science, Artificial Intelligence
Sapana Rani, Raju Halder
Summary: This paper proposes an efficient distortion-free watermarking technique for large-scale datasets in various formats using parallel and distributed computing environment. Experimental evaluation shows performance depends on data format and chosen computing paradigm.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Computer Science, Artificial Intelligence
Myriam Jaouadi, Lotfi Ben Romdhane
Summary: With the rapidly increasing amount of data in social networks, analyzing social networks content has become more challenging. In order to reduce the network's size and preserve the original network's properties, methods such as graph coarsening and graph sampling are gaining attention in the scientific community.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Chemistry, Analytical
Asad Ali Siyal, Eric Sheng-Wen Chen, Hsin-Ju Chan, Reta Birhanu Kitata, Jhih-Ci Yang, Hsiung-Lin Tu, Yu-Ju Chen
Summary: The study presents a sample size-comparable library-based DIA approach, achieving higher protein group identification from small-size library compared to medium-size, large-size, and lung cancer resource spectral library. The approach shows good generality across different instruments and data analysis methods.
ANALYTICAL CHEMISTRY
(2021)
Article
Chemistry, Analytical
Kas J. Houthuijs, Giel Berden, Udo F. H. Engelke, Vasuk Gautam, David S. Wishart, Ron A. Wevers, Jonathan Martens, Jos Oomens
Summary: Infrared ion spectroscopy (IRIS) is increasingly used as an analytical tool for small-molecule identification in conjunction with mass spectrometry (MS). However, directly translating an IR spectrum to a molecular structure remains challenging due to the lack of reference libraries. To solve this issue, an in silico library of vibrational spectra of common MS adducts of over 4500 compounds has been introduced. This library can be queried with experimental IR spectra, enabling accurate identification of metabolites.
ANALYTICAL CHEMISTRY
(2023)
Article
Biochemical Research Methods
Yuling Dai, Robert J. Millikin, Zach Rolfs, Michael R. Shortreed, Lloyd M. Smith
Summary: Tandem mass spectrometry (MS/MS) is widely used for analyzing complex proteomic samples. However, traditional peptide identification methods such as protein sequence database searching and spectral library searching have limitations in discriminating correct and incorrect spectrum assignments and identifying post-translationally modified peptides. To overcome these limitations, a hybrid search strategy that combines protein sequence database and spectral library searches has been developed, along with the use of Global PTM Discovery (G-PTM-D) to generate spectral libraries for various PTMs. This approach improves identification success rates and sensitivity.
JOURNAL OF PROTEOME RESEARCH
(2022)
Article
Biochemical Research Methods
Yuanyue Li, Oliver Fiehn
Summary: This study demonstrates that using flash entropy search can significantly accelerate the speed of mass spectral similarity searches without compromising accuracy. The algorithm allows for quick querying of a large number of spectra, with minimal memory overhead for mass spectrometry laboratories.
Review
Pharmacology & Pharmacy
D. Sala, H. Batebi, K. Ledwitch, P. W. Hildebrand, J. Meiler
Summary: The use of deep machine learning in protein structure prediction allows easy access to annotated conformations, which can compensate for missing experimental structures in structure-based drug discovery. However, the accuracy of these predicted conformations for screening chemical compounds that effectively interact with protein targets is still uncertain. This opinion article examines the benefits and limitations of using state-annotated conformations for ultra-large library screening, particularly for common drug targets like G-protein-coupled receptors.
TRENDS IN PHARMACOLOGICAL SCIENCES
(2023)
Article
Biochemical Research Methods
Ronghui You, Shuwei Yao, Hiroshi Mamitsuka, Shanfeng Zhu
Summary: DeepGraphGO is a multispecies graph neural network-based method aimed at solving the problem of automated function prediction of proteins. By utilizing protein sequence and high-order protein network information, a single model can be trained for all species, providing more training samples for AFP. Experimental results demonstrate that DeepGraphGO significantly outperforms other state-of-the-art methods, including network-based GeneMANIA, deepNF, and clusDCA.
Article
Engineering, Chemical
William R. Cannon, Jeremy D. Zucker, Douglas J. Baxter, Neeraj Kumar, Scott E. Baker, Jennifer M. Hurley, Jay C. Dunlap
Article
Biotechnology & Applied Microbiology
Elena S. Peterson, Lee Ann Mccue, Alexandra C. Schrimpe-Rutledge, Jeffrey L. Jensen, Hyunjoo Walker, Markus A. Kobold, Samantha R. Webb, Samuel H. Payne, Charles Ansong, Joshua N. Adkins, William R. Cannon, Bobbie-Jo M. Webb-Robertson
Article
Computer Science, Theory & Methods
Changjun Wu, Ananth Kalyanaraman, William R. Cannon
IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS
(2012)
Article
Chemistry, Physical
Dennis G. Thomas, Sebastian Jaramillo-Riveri, Douglas J. Baxter, William R. Cannon
JOURNAL OF PHYSICAL CHEMISTRY B
(2014)
Article
Chemistry, Physical
William R. Cannon, Mitchell M. Rawlins
JOURNAL OF PHYSICAL CHEMISTRY C
(2010)
Article
Biochemical Research Methods
William R. Cannon, Mitchell M. Rawlins, Douglas J. Baxter, Stephen J. Callister, Mary S. Lipton, Donald A. Bryant
JOURNAL OF PROTEOME RESEARCH
(2011)
Article
Multidisciplinary Sciences
William R. Cannon
Article
Biochemistry & Molecular Biology
Jennifer M. Hurley, Meaghan S. Jankowski, Hannah De los Santos, Alexander M. Crowell, Samuel B. Fordyce, Jeremy D. Zucker, Neeraj Kumar, Samuel O. Purvine, Errol W. Robinson, Anil Shukla, Erika Zink, William R. Cannon, Scott E. Baker, Jennifer J. Loros, Jay C. Dunlap
Article
Multidisciplinary Sciences
Samuel Britton, Mark Alber, William R. Cannon
JOURNAL OF THE ROYAL SOCIETY INTERFACE
(2020)
Article
Multidisciplinary Sciences
Justin A. North, Adrienne B. Narrowe, Weili Xiong, Kathryn M. Byerly, Guanqi Zhao, Sarah J. Young, Srividya Murali, John A. Wildenthal, William R. Cannon, Kelly C. Wrighton, Robert L. Hettich, F. Robert Tabita
Article
Multidisciplinary Sciences
Bruce J. Palmer, Ann S. Almgren, Connah G. M. Johnson, Andrew T. Myers, William R. Cannon
Summary: High performance computing has the potential to provide significant benefits for investigating biological systems, particularly in studying large modelling problems with many coupled subsystems, such as bacterial cell colonies. BMX is a software system utilizing GPU acceleration to efficiently model the formation of large cell communities under realistic laboratory conditions.
SCIENTIFIC REPORTS
(2023)
Article
Chemistry, Physical
William R. Cannon, Lionel M. Raff
Summary: In 1994, an IUBMB-IUPAC joint committee recommended a revised formulation for standard chemical potentials and reaction free energies to address the multiple charge states of reactants and products in biochemistry. Recent reports challenge the need for such summary formulations, arguing that standard chemical potentials are sufficient for considering different charge state isomers in biochemical reactions.
PHYSICAL CHEMISTRY CHEMICAL PHYSICS
(2021)
Review
Health Care Sciences & Services
Mark Alber, Adrian Buganza Tepole, William R. Cannon, Suvranu De, Salvador Dura-Bernal, Krishna Garikipati, George Karniadakis, William W. Lytton, Paris Perdikaris, Linda Petzold, Ellen Kuhl
NPJ DIGITAL MEDICINE
(2019)
Article
Biochemistry & Molecular Biology
William R. Cannon, Scott E. Baker