Article
Chemistry, Applied
Rocio Galindo-Lujan, Laura Pont, Zoran Minic, Maxim V. Berezovski, Victoria Sanz-Nebot, Fernando Benavente
Summary: This study analyzed the proteins from different varieties of quinoa seeds from Peru and Bolivia using advanced LC-MS/MS technology, identifying protein similarities and differences in the proteome. The comprehensive experimental quinoa seed proteome map presented in this study serves as a valuable starting point for further characterization and nutritional studies of quinoa and quinoa-containing food products.
Article
Biochemistry & Molecular Biology
Delphine Vincent, AnhDuyen Bui, Doris Ram, Vilnis Ezernieks, Frank Bedon, Joe Panozzo, Pankaj Maharjan, Simone Rochfort, Hans Daetwyler, Matthew Hayden
Summary: This study optimized a LC-MS shotgun quantitative proteomics method to screen wheat genotypes for breeding lines with better performance. A large number of wheat proteins were identified using this method, and data mining tools were used to explore the flour proteome.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2022)
Article
Chemistry, Applied
Sridevi Muralidharan, Yan Yee Poon, Graeme C. Wright, Paul A. Haynes, Nanju A. Lee
Summary: This study used mass spectrometry-based proteomic analysis on Australian peanut recombinant inbred lines and found significant protein expression differences between high and low polyphenol expressing RILs. Metabolic changes, including increased enzymatic breakdown of sugars and phenylalanine biosynthesis, were observed in polyphenol-rich RILs. The study also revealed overexpression of phenylpropanoid pathway and antioxidant enzymes, such as catalase, in the polyphenol-rich peanut phenotype.
Article
Biochemical Research Methods
Runmin Yang, Jingjing Ma, Shu Zhang, Yu Zheng, Lusheng Wang, Daming Zhu
Summary: This study introduces a new storage format called mzMD for MS datasets and presents an algorithm to query this format for summarizing a given data window. Experimental results demonstrate the high speed and stability of mzMD in retrieving high-quality data window summaries.
Article
Biochemical Research Methods
Masaki Ishikawa, Ryo Konno, Daisuke Nakajima, Mari Gotoh, Keiko Fukasawa, Hironori Sato, Ren Nakamura, Osamu Ohara, Yusuke Kawashima
Summary: In this study, an ultrafast proteomic method was established using a 5-min gradient LC and quadrupole-Orbitrap MS. By optimizing parameters, the method achieved a high throughput and sensitivity for measuring a large number of samples. The method was demonstrated to be applicable for chemical responsivity screening.
JOURNAL OF PROTEOME RESEARCH
(2022)
Article
Environmental Sciences
Fabio Varriale, Luciana Tartaglione, Sevasti-Kiriaki Zervou, Christopher O. Miles, Hanna Mazur-Marzec, Theodoros M. Triantis, Triantafyllos Kaloudis, Anastasia Hiskia, Carmela Dell'Aversano
Summary: Cyanobacteria produce various bioactive secondary metabolites, including cyanotoxins, which are a global threat to humans and other organisms. Mass spectrometry-based methods have been developed for the determination of microcystins, the most studied class of cyanotoxins. This study compares targeted and untargeted liquid chromatography-mass spectrometry approaches for analyzing cyanobacterial biomass. It also describes the implementation of an analytical workflow for the identification of known and discovery of new cyanopeptides. The study reports the elucidation of new structural variants of microcystins and the proposal of structures for new cyanopeptides.
Article
Biotechnology & Applied Microbiology
Sebastian Didusch, Moritz Madern, Markus Hartl, Manuela Baccarini
Summary: amica is a web-based software that can handle proteomic data and provide quality control, differential expression, biological network, and over-representation analysis. Users can compare multiple conditions and quickly identify enriched or depleted proteins through the interactive query interface. The results can be visualized using customized output graphics and exported in a tab-separated format for sharing.
Article
Biochemical Research Methods
Jinjun Gao, Yuan Liu, Fan Yang, Xuemin Chen, Benjamin F. Cravatt, Chu Wang
Summary: ABPP is a powerful chemical proteomic method for studying protein activity, modifications, and interactions, where accurate quantification is crucial. CIMAGE is a specialized quantification software for ABPP data analysis, providing efficient and accurate quantification with the ability to visualize results conveniently.
JOURNAL OF PROTEOME RESEARCH
(2021)
Article
Biochemistry & Molecular Biology
Wen-Jen Lin, Pei-Chun Shen, Hsiu-Cheng Liu, Yi-Chun Cho, Min-Kung Hsu, I-Chen Lin, Fang-Hsin Chen, Juan-Cheng Yang, Wen-Lung Ma, Wei-Chung Cheng
Summary: LipidSig is a flexible and user-friendly web server designed to help users identify significant lipid-related features and advance the field of lipid biology through efficient data analysis and exploration of lipid characteristics.
NUCLEIC ACIDS RESEARCH
(2021)
Article
Biology
Ghizal Siddiqui, Amanda De Paoli, Christopher A. MacRaild, Anna E. Sexton, Coralie Boulet, Anup D. Shah, Mitchell B. Batty, Ralf B. Schittenhelm, Teresa G. Carvalho, Darren J. Creek
Summary: A comprehensive spectral library for Plasmodium falciparum-infected RBCs has been created, measuring the abundance of peptides from both the parasite and RBC proteins. This library includes proteins from different RBC stages, the RBC compartment of trophozoite-iRBCs, and cytosolic fraction from uninfected RBCs. By using this library, semi-quantitative proteomics datasets have been generated to characterize different asexual parasite stages and compare drug-resistant and drug-sensitive parasites.
Article
Biochemistry & Molecular Biology
Ana Gonzalez Abril, Pilar Calo-Mata, Karola Bohme, Tomas G. Villa, Jorge Barros-Velazquez, Manuel Pazos, Monica Carrera
Summary: In this study, shotgun proteomics was used to characterize biogenic-amine-producing bacteria, revealing protein networks and pathways related to energy, putrescine metabolism, and host-virus interaction. Species-specific peptide biomarkers were also identified for bacterial identification. These findings have important implications for the treatment of food intoxication and microbial source tracking.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2023)
Article
Anthropology
Manasij Pal Chowdhury, Stuart Campbell, Michael Buckley
Summary: Archaeological ceramics are a valuable source of ancient biomolecules for studying ancient diet, with traditional lipid analysis methods having limitations in identifying all resources. Proteomic analysis using LC-MS/MS technology has proven to be more comprehensive in identifying resources in ceramics, providing evidence of soybean products in the Middle East by the mid-second millennium BCE.
JOURNAL OF ARCHAEOLOGICAL SCIENCE
(2021)
Article
Biochemical Research Methods
Neil A. McCracken, Sarah A. Peck Justice, Aruna B. Wijeratne, Amber L. Mosley
Summary: The study introduces a user-friendly analysis of the melt shift calculation workflow and quantitatively assesses the impact of key steps in the analysis workflow on the final output list of stabilized and destabilized proteins. It also presents a more optimized analysis workflow, illustrating the importance of selected calculation steps on the final list of reported proteins of interest in a study. The development of the R based program Inflect offers a valuable resource for the research community to analyze data from TPP and CETSA experiments.
JOURNAL OF PROTEOME RESEARCH
(2021)
Article
Biochemistry & Molecular Biology
Diana Canetti, Francesca Brambilla, Nigel B. Rendell, Paola Nocerino, Janet A. Gilbertson, Dario Di Silvestre, Andrea Bergamaschi, Francesca Lavatelli, Giampaolo Merlini, Julian D. Gillmore, Vittorio Bellotti, Pierluigi Mauri, Graham W. Taylor
Summary: Amyloidosis is a rare human disease caused by abnormal protein deposition in tissues, with proteomic analysis playing a crucial role in clinical diagnosis and amyloid typing. Inter-center data exchange is effective for testing and validating the accuracy of different software platforms in proteomics analysis.
Article
Biochemical Research Methods
Chenxin Li, Mingxuan Gao, Wenxian Yang, Chuanqi Zhong, Rongshan Yu
Summary: Diamond is a multi-modal DIA-MS data processing pipeline based on Nextflow and containerization, integrating SCS and PCS strategies for cases with and without assay libraries. This versatile toolbox enables large-scale peptide identification and quantification in DIA data, while being user-friendly and easily extendable.
Article
Biochemical Research Methods
Sepideh Mazrouee, Wei Wang
IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS
(2020)
Article
Biochemical Research Methods
J. Harry Caufield, John Fu, Ding Wang, Vladimir Guevara-Gonzalez, Wei Wang, Peipei Ping
Summary: Proteomics aims to study protein features in entire systems, with various resources available to make results more discoverable, accessible, interoperable, and reusable. Linking specific terms, identifiers, and texts can unify individual data points, potentially revealing new relationships and maximizing the value of datasets and methods for the proteomics community and beyond.
JOURNAL OF PROTEOME RESEARCH
(2021)
Article
Computer Science, Theory & Methods
Youfu Li, Matteo Interlandi, Fotis Psallidas, Wei Wang, Carlo Zaniolo
Summary: Many DISC systems provide easy-to-use APIs and efficient scheduling and execution strategies for building concise data-parallel programs. However, some crucial features and optimizations are not well-supported, requiring runtime dataflow states to achieve.
IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS
(2021)
Article
Biochemical Research Methods
Jyun-Yu Jiang, Chelsea J-T Ju, Junheng Hao, Muhao Chen, Wei Wang
Summary: circRNA is a novel class of long non-coding RNAs that play important roles in gene regulation and disease association. The JEDI framework, utilizing deep learning and a cross-attention layer, effectively predicts circRNAs, outperforming existing methods significantly.
Article
Multidisciplinary Sciences
Jyun-Yu Jiang, Yichao Zhou, Xiusi Chen, Yan-Ru Jhou, Liqi Zhao, Sabrina Liu, Po-Chun Yang, Jule Ahmar, Wei Wang
Summary: This paper proposes a method to leverage social media users as social sensors, predicting pandemic trends while suggesting potential risk factors for public health experts. The method utilizes deep learning models to recognize important entities and their relations, establishing dynamic heterogeneous graphs to describe the observations of social media users. A web-based system is also developed to allow easy interaction for domain experts without computer science backgrounds.
PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES
(2022)
Article
Computer Science, Information Systems
Justin Wood, Corey Arnold, Wei Wang
Summary: Recent work suggests incorporating knowledge sources into the topic modeling process to improve topic discovery. However, existing semi-supervised topic models assume that the corpus contains topics on a subset of a domain, leading to slow inference when considering a large number of article-topics. This paper presents a ranking technique based on the PageRank algorithm to speed up the inference process and improve perplexity and interpretability. The results show significant improvements in various evaluation metrics compared to baseline methods.
Article
Biochemistry & Molecular Biology
Megan J. Agajanian, Frances M. Potjewyd, Brittany M. Bowman, Smaranda Solomon, Kyle M. LaPak, Dhaval P. Bhatt, Jeffery L. Smith, Dennis Goldfarb, Alison D. Axtman, Michael B. Major
Summary: This study reveals that CSNK1 gamma 3 activates the beta-catenin-dependent WNT signaling pathway and induces phosphorylation of low-density lipoprotein receptor-related protein 6. While the expression of CSNK1 gamma 3 can drive WNT pathway activity, potential functional redundancy within the family necessitates the loss of all three family members to suppress WNT signaling pathway.
JOURNAL OF BIOLOGICAL CHEMISTRY
(2022)
Proceedings Paper
Computer Science, Artificial Intelligence
Seungbae Kim, Jyun-Yu Jiang, Wei Wang
Summary: In this study, the SPoD model is proposed to detect undisclosed sponsorship in social media posts by learning various aspects of the posts. The experimental results demonstrate that SPoD significantly out-performs existing baseline methods in discovering sponsored posts on social media.
WSDM '21: PROCEEDINGS OF THE 14TH ACM INTERNATIONAL CONFERENCE ON WEB SEARCH AND DATA MINING
(2021)
Proceedings Paper
Computer Science, Information Systems
Justin Wood, Wei Wang, Corey Arnold
Summary: This paper introduces a new interpretation of nonparametric Bayesian learning called the biased coin flip process, proving its equivalence to the Dirichlet process and demonstrating improved predictive performance.
DOCUMENT ANALYSIS AND RECOGNITION - ICDAR 2021, PT II
(2021)
Proceedings Paper
Computer Science, Artificial Intelligence
Junheng Hao, Chuan Lei, Vasilis Efthymiou, Abdul Quamar, Fatma Ozcan, Yizhou Sun, Wei Wang
Summary: Medical ontologies and databases often have discrepancies that compromise interoperability, requiring data to ontology matching. Existing solutions focus on extracting information from ontologies for engineering, which can be labor-intensive. The proposed MEDTO framework utilizes three innovative techniques to achieve significant improvements in data to ontology matching.
KDD '21: PROCEEDINGS OF THE 27TH ACM SIGKDD CONFERENCE ON KNOWLEDGE DISCOVERY & DATA MINING
(2021)
Proceedings Paper
Computer Science, Artificial Intelligence
Zijie Huang, Yizhou Sun, Wei Wang
Summary: Many real-world systems are dynamic in nature, where coupled objects interact through graphs and exhibit complex behavior over time. The COVID-19 pandemic can be seen as a dynamic system with geographical locations as objects, influencing each other's infection rates. There is a need to explore how to accurately model and predict the complex dynamics of these systems.
KDD '21: PROCEEDINGS OF THE 27TH ACM SIGKDD CONFERENCE ON KNOWLEDGE DISCOVERY & DATA MINING
(2021)
Proceedings Paper
Computer Science, Artificial Intelligence
Cheng Zheng, Bo Zong, Wei Cheng, Dongjin Song, Jingchao Ni, Wenchao Yu, Haifeng Chen, Wei Wang
Summary: The proposed TSNet model jointly learns temporal and structural features for node classification from sparsified temporal graphs, effectively extracting local features and optimizing node representations to improve performance in node classification tasks.
MACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES, ECML PKDD 2020, PT III
(2021)
Proceedings Paper
Computer Science, Information Systems
Yichao Zhou, Wei-Ting Chen, Bowen Zhang, David Lee, J. Harry Caufield, Kai-Wei Chang, Yizhou Sun, Peipei Ping, Wei Wang
Summary: The paper introduces CREATe, a novel computational resource platform for extracting, indexing, and querying the contents of clinical case reports, fostering an environment of sustainable resource support and discovery, and helping researchers overcome challenges in information science.
2021 IEEE 37TH INTERNATIONAL CONFERENCE ON DATA ENGINEERING (ICDE 2021)
(2021)
Proceedings Paper
Computer Science, Artificial Intelligence
Yichao Zhou, Jyun-yu Jiang, Jieyu Zhao, Kai-Wei Chang, Wei Wang
58TH ANNUAL MEETING OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS (ACL 2020)
(2020)
Article
Computer Science, Information Systems
Cheng Zheng, Qin Zhang, Guodong Long, Chengqi Zhang, Sean D. Young, Wei Wang
