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Article ; Online: BTR: a bioinformatics tool recommendation system.

Green, Ryan / Qu, Xufeng / Liu, Jinze / Yu, Tingting

2024 Volume 40, Issue 5

Abstract: Motivation: The rapid expansion of Bioinformatics research has led to a proliferation of computational tools for scientific analysis pipelines. However, constructing these pipelines is a demanding task, requiring extensive domain knowledge and careful ... ...

Abstract	Motivation: The rapid expansion of Bioinformatics research has led to a proliferation of computational tools for scientific analysis pipelines. However, constructing these pipelines is a demanding task, requiring extensive domain knowledge and careful consideration. As the Bioinformatics landscape evolves, researchers, both novice and expert, may feel overwhelmed in unfamiliar fields, potentially leading to the selection of unsuitable tools during workflow development. Results: In this article, we introduce the Bioinformatics Tool Recommendation system (BTR), a deep learning model designed to recommend suitable tools for a given workflow-in-progress. BTR leverages recent advances in graph neural network technology, representing the workflow as a graph to capture essential context. Natural language processing techniques enhance tool recommendations by analyzing associated tool descriptions. Experiments demonstrate that BTR outperforms the existing Galaxy tool recommendation system, showcasing its potential to streamline scientific workflow construction. Availability and implementation: The Python source code is available at https://github.com/ryangreenj/bioinformatics_tool_recommendation.
MeSH term(s)	Computational Biology/methods ; Software ; Workflow ; Deep Learning ; Natural Language Processing
Language	English
Publishing date	2024-04-25
Publishing country	England
Document type	Journal Article
ZDB-ID	1422668-6
ISSN	1367-4811 ; 1367-4803
ISSN (online)	1367-4811
ISSN	1367-4803
DOI	10.1093/bioinformatics/btae275
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Article ; Online: N-Level Hierarchy-Based Optimal Control to Develop Therapeutic Strategies for Ecological Evolutionary Dynamics Systems.

Liu, Jinze / Sun, Jiayue / Zhang, Huaguang / Xu, Shun / Zou, Zifang

IEEE transactions on neural networks and learning systems

2024 Volume 35, Issue 3, Page(s) 3953–3963

Abstract: This article mainly proposes an evolutionary algorithm and its first application to develop therapeutic strategies for ecological evolutionary dynamics systems (EEDS), obtaining the balance between tumor cells and immune cells by rationally arranging ... ...

Abstract	This article mainly proposes an evolutionary algorithm and its first application to develop therapeutic strategies for ecological evolutionary dynamics systems (EEDS), obtaining the balance between tumor cells and immune cells by rationally arranging chemotherapeutic drugs and immune drugs. First, an EEDS nonlinear kinetic model is constructed to describe the relationship between tumor cells, immune cells, dose, and drug concentration. Second, the N-level hierarchy optimization (NLHO) algorithm is designed and compared with five algorithms on 20 benchmark functions, which proves the feasibility and effectiveness of NLHO. Finally, we apply NLHO into EEDS to give a dynamic adaptive optimal control policy and develop therapeutic strategies to reduce tumor cells, while minimizing the harm of chemotherapy drugs and immune drugs to the human body. The experimental results prove the validity of the research method.
MeSH term(s)	Humans ; Neural Networks, Computer ; Algorithms ; Benchmarking ; Biological Evolution ; Research Design
Language	English
Publishing date	2024-02-29
Publishing country	United States
Document type	Journal Article
ISSN	2162-2388
ISSN (online)	2162-2388
DOI	10.1109/TNNLS.2022.3201517
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Article ; Online: scFed: federated learning for cell type classification with scRNA-seq.

Wang, Shuang / Shen, Bochen / Guo, Lanting / Shang, Mengqi / Liu, Jinze / Sun, Qi / Shen, Bairong

Briefings in bioinformatics

2024 Volume 25, Issue 1

Abstract: The advent of single-cell RNA sequencing (scRNA-seq) has revolutionized our understanding of cellular heterogeneity and complexity in biological tissues. However, the nature of large, sparse scRNA-seq datasets and privacy regulations present challenges ... ...

Abstract	The advent of single-cell RNA sequencing (scRNA-seq) has revolutionized our understanding of cellular heterogeneity and complexity in biological tissues. However, the nature of large, sparse scRNA-seq datasets and privacy regulations present challenges for efficient cell identification. Federated learning provides a solution, allowing efficient and private data use. Here, we introduce scFed, a unified federated learning framework that allows for benchmarking of four classification algorithms without violating data privacy, including single-cell-specific and general-purpose classifiers. We evaluated scFed using eight publicly available scRNA-seq datasets with diverse sizes, species and technologies, assessing its performance via intra-dataset and inter-dataset experimental setups. We find that scFed performs well on a variety of datasets with competitive accuracy to centralized models. Though Transformer-based model excels in centralized training, its performance slightly lags behind single-cell-specific model within the scFed framework, coupled with a notable time complexity concern. Our study not only helps select suitable cell identification methods but also highlights federated learning's potential for privacy-preserving, collaborative biomedical research.
MeSH term(s)	Single-Cell Gene Expression Analysis ; Learning ; Algorithms ; Benchmarking ; Biomedical Research ; Sequence Analysis, RNA
Language	English
Publishing date	2024-01-15
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2068142-2
ISSN	1477-4054 ; 1467-5463
ISSN (online)	1477-4054
ISSN	1467-5463
DOI	10.1093/bib/bbad507
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Article ; Online: A new deep learning framework to process Matrix-assisted Laser Desorption/Ionisation Mass Spectrometry Imaging (MALDI-MSI) data of Tissue Microarrays (TMAs).

Wangyan, Tingyi / Sun, Qi / Grizzard, Pamela / Liu, Jinze / Peng, Yifan

AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science

2023 Volume 2023, Page(s) 554–561

Abstract: Matrix-Assisted Laser Desorption Ionization mass spectrometry imaging (MALDI-MSI) is a mass spectrometry ionization technique that can be used to directly analyze tissues and has led the way in the development of biological and clinical applications for ... ...

Abstract	Matrix-Assisted Laser Desorption Ionization mass spectrometry imaging (MALDI-MSI) is a mass spectrometry ionization technique that can be used to directly analyze tissues and has led the way in the development of biological and clinical applications for imaging mass spectrometry. One of its advantages is measuring the distribution of a large number of analytes at one time without destroying the sample, making it a useful method in tissue-based studies. However, analysis of the MALDI-MSI images from tissue microarrays (TMAs) remains less studied. While several automated systems have been developed for tissue classification (e.g., cancer vs non-cancer), they process the MALDI data at the measuring point level, which ignores spatial relationships among individual points within the tissue sample. In this work, we propose mNet, a new deep learning framework to analyze MALDI-MSI data of TMAs at the tissue-needle-core level to ensure that the samples maintain their original spatial context. In addition, we introduced data augmentation techniques to increase data size which is often limited in biomedical data. We applied our framework to analyzing TMAs from breast and lung cancer. We found that our framework outperforms conventional machine learning methods in the challenging race detection task. The results highlight the potential of deep learning to assist pathologists in analyzing tissue specimens in a label-free, high-throughput manner.
Language	English
Publishing date	2023-06-16
Publishing country	United States
Document type	Journal Article
ZDB-ID	2676378-3
ISSN	2153-4063 ; 2153-4063
ISSN (online)	2153-4063
ISSN	2153-4063
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Article ; Online: Long-read sequencing of the zebrafish genome reorganizes genomic architecture.

Chernyavskaya, Yelena / Zhang, Xiaofei / Liu, Jinze / Blackburn, Jessica

BMC genomics

2022 Volume 23, Issue 1, Page(s) 116

Abstract: Background: Nanopore sequencing technology has revolutionized the field of genome biology with its ability to generate extra-long reads that can resolve regions of the genome that were previously inaccessible to short-read sequencing platforms. Over 50% ...

Abstract	Background: Nanopore sequencing technology has revolutionized the field of genome biology with its ability to generate extra-long reads that can resolve regions of the genome that were previously inaccessible to short-read sequencing platforms. Over 50% of the zebrafish genome consists of difficult to map, highly repetitive, low complexity elements that pose inherent problems for short-read sequencers and assemblers. Results: We used long-read nanopore sequencing to generate a de novo assembly of the zebrafish genome and compared our assembly to the current reference genome, GRCz11. The new assembly identified 1697 novel insertions and deletions over one kilobase in length and placed 106 previously unlocalized scaffolds. We also discovered additional sites of retrotransposon integration previously unreported in GRCz11 and observed the expression of these transposable elements in adult zebrafish under physiologic conditions, implying they have active mobility in the zebrafish genome and contribute to the ever-changing genomic landscape. Conclusions: We used nanopore sequencing to improve upon and resolve the issues plaguing the current zebrafish reference assembly, GRCz11. Zebrafish is a prominent model of human disease, and our corrected assembly will be useful for studies relying on interspecies comparisons and precise linkage of genetic events to disease phenotypes.
MeSH term(s)	Animals ; Genome ; Genomics ; High-Throughput Nucleotide Sequencing ; Humans ; Nanopores ; Sequence Analysis, DNA ; Zebrafish/genetics
Language	English
Publishing date	2022-02-10
Publishing country	England
Document type	Journal Article
ZDB-ID	2041499-7
ISSN	1471-2164 ; 1471-2164
ISSN (online)	1471-2164
ISSN	1471-2164
DOI	10.1186/s12864-022-08349-3
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Article ; Online: Research Progress of Lytic Chitin Monooxygenase and Its Utilization in Chitin Resource Fermentation Transformation

Pan, Delong / Liu, Jinze / Xiao, Peiyao / Xie, Yukun / Zhou, Xiuling / Zhang, Yang

Fermentation. 2023 Aug. 13, v. 9, no. 8

2023

Abstract: Every year, seafood waste produced globally contains about 10 million tons of wasted crab, shrimp and lobster shells, which are rich in chitin resources. The exploitation and utilization of chitin resources are of great significance to environmental ... ...

Abstract	Every year, seafood waste produced globally contains about 10 million tons of wasted crab, shrimp and lobster shells, which are rich in chitin resources. The exploitation and utilization of chitin resources are of great significance to environmental protection, economic development and sustainable development. Lytic polysaccharide monooxygenases (LPMOs) can catalyze polysaccharides by oxidative breakage of glycosidic bonds and have catalytic activity for chitin and cellulose, so they play an important role in the transformation of refractory polysaccharides into biomass. Although there have been many studies related to LPMOs, the research related to lytic chitin monooxygenases (LCMs) is still very limited. The specific catalytic mechanism of LCMs has not been fully elucidated, which poses a challenge to their application in industrial biomass conversion. This review introduces the present situation of resource development and utilization in chitin, the origin and classification of different LCMs families, the structural characteristics of LCMs and the relationship between structure and function. The research results related to activity detection, screening, preparation and transformation of LCMs were summarized and discussed. Finally, the synergistic effect of LCMs and chitin enzyme on biomass degradation was reviewed, and the existing problems and future research directions were pointed out. This is the first review focusing on Chitin-Active LPMOs in recent years, intending to provide a reference for applying chitin degradation enzymes system in the industry.
Keywords	biomass ; catalytic activity ; cellulose ; chitin ; crabs ; environmental protection ; enzymes ; fermentation ; industry ; lobsters ; resource management ; seafood waste ; shrimp ; sustainable development ; synergism
Language	English
Dates of publication	2023-0813
Publishing place	Multidisciplinary Digital Publishing Institute
Document type	Article ; Online
ZDB-ID	2813985-9
ISSN	2311-5637
ISSN	2311-5637
DOI	10.3390/fermentation9080754
Database	NAL-Catalogue (AGRICOLA)

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Article ; Online: A reference-free approach for cell type classification with scRNA-seq.

Sun, Qi / Peng, Yifan / Liu, Jinze

iScience

2021 Volume 24, Issue 8, Page(s) 102855

Abstract: Single-cell RNA sequencing (scRNA-seq) has become a revolutionary technology to characterize cells under different biological conditions. Unlike bulk RNA-seq, gene expression from scRNA-seq is highly sparse due to limited sequencing depth per cell. This ... ...

Abstract	Single-cell RNA sequencing (scRNA-seq) has become a revolutionary technology to characterize cells under different biological conditions. Unlike bulk RNA-seq, gene expression from scRNA-seq is highly sparse due to limited sequencing depth per cell. This is worsened by tossing away a significant portion of reads that attribute to gene quantification. To overcome data sparsity and fully utilize original reads, we propose scSimClassify, a reference-free and alignment-free approach to classify cell types with
Language	English
Publishing date	2021-07-14
Publishing country	United States
Document type	Journal Article
ISSN	2589-0042
ISSN (online)	2589-0042
DOI	10.1016/j.isci.2021.102855
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Article ; Online: Persistent PKA activation redistributes NaV1.5 to the cell surface of adult rat ventricular myocytes.

Bernas, Tytus / Seo, John / Wilson, Zachary T / Tan, Bi-Hua / Deschenes, Isabelle / Carter, Christiane / Liu, Jinze / Tseng, Gea-Ny

The Journal of general physiology

2024 Volume 156, Issue 2

Abstract: During chronic stress, persistent activation of cAMP-dependent protein kinase (PKA) occurs, which can contribute to protective or maladaptive changes in the heart. We sought to understand the effect of persistent PKA activation on NaV1.5 channel ... ...

Abstract	During chronic stress, persistent activation of cAMP-dependent protein kinase (PKA) occurs, which can contribute to protective or maladaptive changes in the heart. We sought to understand the effect of persistent PKA activation on NaV1.5 channel distribution and function in cardiomyocytes using adult rat ventricular myocytes as the main model. PKA activation with 8CPT-cAMP and okadaic acid (phosphatase inhibitor) caused an increase in Na+ current amplitude without altering the total NaV1.5 protein level, suggesting a redistribution of NaV1.5 to the myocytes' surface. Biotinylation experiments in HEK293 cells showed that inhibiting protein trafficking from intracellular compartments to the plasma membrane prevented the PKA-induced increase in cell surface NaV1.5. Additionally, PKA activation induced a time-dependent increase in microtubule plus-end binding protein 1 (EB1) and clustering of EB1 at myocytes' peripheral surface and intercalated discs (ICDs). This was accompanied by a decrease in stable interfibrillar microtubules but an increase in dynamic microtubules along the myocyte surface. Imaging and coimmunoprecipitation experiments revealed that NaV1.5 interacted with EB1 and β-tubulin, and both interactions were enhanced by PKA activation. We propose that persistent PKA activation promotes NaV1.5 trafficking to the peripheral surface of myocytes and ICDs by providing dynamic microtubule tracks and enhanced guidance by EB1. Our proposal is consistent with an increase in the correlative distribution of NaV1.5, EB1, and β-tubulin at these subcellular domains in PKA-activated myocytes. Our study suggests that persistent PKA activation, at least during the initial phase, can protect impulse propagation in a chronically stressed heart by increasing NaV1.5 at ICDs.
MeSH term(s)	Animals ; Humans ; Rats ; Cell Membrane ; Cluster Analysis ; HEK293 Cells ; Myocytes, Cardiac ; Tubulin ; Protein Kinases/metabolism ; NAV1.5 Voltage-Gated Sodium Channel/metabolism
Chemical Substances	Tubulin ; Protein Kinases (EC 2.7.-) ; Scn5a protein, rat ; NAV1.5 Voltage-Gated Sodium Channel
Language	English
Publishing date	2024-01-16
Publishing country	United States
Document type	Journal Article
ZDB-ID	3118-5
ISSN	1540-7748 ; 0022-1295
ISSN (online)	1540-7748
ISSN	0022-1295
DOI	10.1085/jgp.202313436
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Article: Engineering cGAS-agonistic oligonucleotides as therapeutics for cancer immunotherapy.

Zhou, Shurong / Su, Ting / Cheng, Furong / Cole, Janet / Liu, Xiang / Zhang, Bei / Alam, Shaheer / Liu, Jinze / Zhu, Guizhi

Molecular therapy. Nucleic acids

2024 Volume 35, Issue 1, Page(s) 102126

Abstract: Activating cyclic GMP-AMP synthase-stimulator of interferon genes (cGAS-STING) holds great potential for cancer immunotherapy by eliciting type-I interferon (IFN-I) responses. Yet, current approaches to cGAS-STING activation rely on STING agonists, which ...

Abstract	Activating cyclic GMP-AMP synthase-stimulator of interferon genes (cGAS-STING) holds great potential for cancer immunotherapy by eliciting type-I interferon (IFN-I) responses. Yet, current approaches to cGAS-STING activation rely on STING agonists, which suffer from difficult formulation, poor pharmacokinetics, and marginal clinical therapeutic efficacy. Here, we report nature-inspired oligonucleotide, Svg3, as a cGAS agonist for cGAS-STING activation in tumor combination immunotherapy. The hairpin-shaped Svg3 strongly binds to cGAS and enhances phase separation to form Svg3-cGAS liquid-like droplets. This results in cGAS-specific immunoactivation and robust IFN-I responses. Remarkably, Svg3 outperforms several state-of-the-art STING agonists in murine and human cells/tissues. Nanoparticle-delivered Svg3 reduces tumor immunosuppression and potentiates immune checkpoint blockade therapeutic efficacy of multiple syngeneic tumor models in wild-type mice, but in neither
Language	English
Publishing date	2024-01-24
Publishing country	United States
Document type	Journal Article
ZDB-ID	2662631-7
ISSN	2162-2531
ISSN	2162-2531
DOI	10.1016/j.omtn.2024.102126
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Article ; Online: Structural characterisation of deer sinew peptides as calcium carriers, their promotion of MC3T3-E1 cell proliferation and their effect on bone deposition in mice.

Sun, Li / Liu, Jinze / Pei, Hongyan / Shi, Meiling / Chen, Weijia / Zong, Ying / Zhao, Yan / Li, Jianming / Du, Rui / He, Zhongmei

Food & function

2024 Volume 15, Issue 5, Page(s) 2587–2603

Abstract: Deer sinew as a by-product has high collagen and nutritional value. This study focuses on its hydrolysate being used as a calcium carrier to develop functional foods. The chelation mechanism was analyzed by SEM, EDS, UV-vis, FTIR, and fluorescence ... ...

Abstract	Deer sinew as a by-product has high collagen and nutritional value. This study focuses on its hydrolysate being used as a calcium carrier to develop functional foods. The chelation mechanism was analyzed by SEM, EDS, UV-vis, FTIR, and fluorescence spectroscopy and zeta potential analysis after using peptide-sequenced deer sinew peptides for chelation with calcium ions. The results showed that the chelation of deer sinew peptides with calcium ions occurs mainly at the O and N atoms of carboxyl, amino and amide bonds.
MeSH term(s)	Mice ; Animals ; Calcium/metabolism ; Deer/metabolism ; Cell Proliferation ; Calcium, Dietary/metabolism ; Peptides/pharmacology ; Peptides/metabolism ; Ions/metabolism ; Ions/pharmacology ; Osteoblasts
Chemical Substances	Calcium (SY7Q814VUP) ; Calcium, Dietary ; Peptides ; Ions
Language	English
Publishing date	2024-03-04
Publishing country	England
Document type	Journal Article
ZDB-ID	2612033-1
ISSN	2042-650X ; 2042-6496
ISSN (online)	2042-650X
ISSN	2042-6496
DOI	10.1039/d3fo04627c
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