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Physicochemical and structural properties of starches from non-traditional sources in China

Food Science and Human Wellness 2023年第2期12卷 416-423页

作者： Jingyi Yang Chagam Koteswara Reddy Zhili Fan Baojun Xu Food Science and Technology Program BNU-HKBU United International CollegeZhuhai 519087China Department of Biochemistry and Bioinformatics Institute of ScienceGITAM(Deemed to be University)Visakhapatnam 530045India

In this study,we isolated starches from non-traditional sources,including quinoa,lentil,arrowhead,gorgon fruit,sorghum,chickpea,proso millet,and purple potato and investigated their morphology,physicochemical,and functional *** differences in starch particle morphology,swelling power,solubility,syneresis,crystalline pattern,and pasting viscosity were observed among the starches from these nontraditional ***,all these isolated starches had unique properties because of their characteristic distinct granules when seen under scanning electron microscopy(SEM).The amylose content of the isolated starches shown significant difference(P<0.05),and the values ranged between 11.46%and 37.61%.Results demonstrated that the isolated starches contained between 79.82%to 86.56%starch,indicating that the isolated starches had high purity.X-ray diffraction(XRD)patterns of starches isolated from sorghum,proso millet,quinoa,purple potato,and gorgon fruit presented A-type diffraction pattern;while lentil seeds,arrowhead,and chickpea starches presented C-type diffraction ***,these results will promote the development of products based on starch isolated from non-traditional starches.

关键词： Starch Viscosity Morphology Quinoa Sorghum Proso millet

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Modeling the causal regulatory network by integrating chromatin accessibility and transcriptome data

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National Science Review 2016年第2期3卷 240-251页

作者： Yong Wang Rui Jiang Wing Hung Wong Department of Statistics Department of Biomedical Data ScienceBio-X ProgramStanford University Academy of Mathematics and Systems Science National Center for Mathematics and Interdisciplinary SciencesChinese Academy of Sciences MOE Key Laboratory of Bioinformatics Bioinformatics Division and Center for Synthetic and Systems BiologyTNLISTDepartment of AutomationTsinghua University

Cell packs a lot of genetic and regulatory information through a structure known as chromatin,*** is wrapped around histone proteins and is tightly packed in a remarkable *** express a gene in a specific coding region,the chromatin would open up and DNA loop may be formed by interacting enhancers and ***,the mediator and cohesion complexes,sequence-specific transcription factors,and RNA polymerase Ⅱ are recruited and work together to elaborately regulate the expression *** is in pressing need to understand how the information,about when,where,and to what degree genes should be expressed,is embedded into chromatin structure and gene regulatory *** to large consortia such as Encyclopedia of DNA Elements(ENCODE) and Roadmap Epigenomic projects,extensive data on chromatin accessibility and transcript abundance are available across many tissues and cell *** rich data offer an exciting opportunity to model the causal regulatory ***,we will review the current experimental approaches,foundational data,computational problems,interpretive frameworks,and integrative models that will enable the accurate interpretation of regulatory ***,we will discuss the efforts to organize,analyze,model,and integrate the DNA accessibility data,transcriptional data,and functional genomic regions *** believe that these efforts will eventually help us understand the information flow within the cell and will influence research directions across many fields.

关键词： gene regulatory network open chromatin DNA accessibility transcription factor colocalization statistical model data integration

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Computational systems biology of metabolism in single- and multi- species microbial systems

Computational systems biology of metabolism in single- and m...

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Liaison Functions 2014 - Core programming Area at the 2014 AIChE Annual Meeting

作者： Zomorrodi, Ali R. Department of Biomedical Engineering Graduate Program in Bioinformatics Boston University BostonMA United States

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Breaking the high-throughput bottleneck

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Scientific Computing 2006年第4期23卷 22-26页

作者： Waters, Katrina M. Singhal, Mudita Webb-Robertson, Bobbie-Jo M. Stephan, Eric G. Gephart, Julie M. Computational Biology and Bioinformatics Groups United States Lab's Systems Biology Program Biological Sciences Division United States PNNL United States

The development of high-throughput (HTP) technologies such as transcriptomics (microarrays) and proteomics has made a revolution in the medical industry. PNNL is developing a systems biology computational framework using a problem-solving environment called bioinformatics Resource Manager (BRM) that automates routine data-merging and data-mining methods, and provides seamless linkage to data visualization tools. The BRM is designed to be operated by biologists looking for greater insights into their experimental results. BRM uses Remote Method Invocation (RMI) to launch several external data analysis tools, including NCBI's PubMed, the Conserved Domain Architectural Retrieval Tool (CDART) and the Basic Local Alignment Search Tool (BLAST). PQuad is a proteomics visualization tool that combines DNA or RNA sequence and proteomics data at multiple resolutions. It enables visualization of the data at the chromosome, gene and sequence levels.

关键词： Data visualization

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Protein subcellular localization prediction of eukaryotes using a knowledge-based approach

Protein subcellular localization prediction of eukaryotes us...

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8th International Conference on bioinformatics: bioinformatics, InCoB 2009

作者： Lin, Hsin-Nan Chen, Ching-Tai Sung, Ting-Yi Ho, Shinn-Ying Hsu, Wen-Lian Bioinformatics Program Academia Sinica Taipei Taiwan Bioinformatics Lab. Institute of Information Science Academia Sinica Taipei Taiwan Institute of Bioinformatics National Chiao Tung University Hsinchu Taiwan

Background: The study of protein subcellular localization (PSL) is important for elucidating protein functions involved in various cellular processes. However, determining the localization sites of a protein through wet-lab experiments can be time-consuming and labor-intensive. Thus, computational approaches become highly desirable. Most of the PSL prediction systems are established for single-localized proteins. However, a significant number of eukaryotic proteins are known to be localized into multiple subcellular organelles. Many studies have shown that proteins may simultaneously locate or move between different cellular compartments and be involved in different biological processes with different roles. Results: In this study, we propose a knowledge based method, called KnowPredsite, to predict the localization site(s) of both single-localized and multi-localized proteins. Based on the local similarity, we can identify the "related sequences" for prediction. We construct a knowledge base to record the possible sequence variations for protein sequences. When predicting the localization annotation of a query protein, we search against the knowledge base and used a scoring mechanism to determine the predicted sites. We downloaded the dataset from ngLOC, which consisted of ten distinct subcellular organelles from 1923 species, and performed ten-fold cross validation experiments to evaluate KnowPred site's performance. The experiment results show that KnowPredsite achieves higher prediction accuracy than ngLOC and Blast-hit method. For singlelocalized proteins, the overall accuracy of KnowPredsite is 91.7%. For multi-localized proteins, the overall accuracy of KnowPred site is 72.1%, which is significantly higher than that of ngLOC by 12.4%. Notably, half of the proteins in the dataset that cannot find any Blast hit sequence above a specified threshold can still be correctly predicted by KnowPredsite. Conclusion: KnowPredsite demonstrates the power of identifying re

关键词： Proteins

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It takes glue to tango: MeDICi integration framework's data-intensive computing pipeline

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Scientific Computing 2008年第7期25卷 16-19页

作者： Gorton, Ian Oehmen, Christopher S. McDermott, Hason E. PNNL's Data Intensive Computing Program United States Laboratory's Bioinformatics and Computational Biology Group Fundamental and Computational Sciences Directorate United States

Researchers at the Department of Energy's (DOE) Pacific Northwest National Laboratory (PNNL) in Richland, WA, are creating computing environments for biologists that seamlessly integrate collections of data and computational resources. MeDICi is an evolving middleware platform for building complex, high-performance analytical applications. MIF components are constructed using Java programming interfaces that support inter-component communication using asynchronous messaging. Local components execute inside the MIF container. Remote components create distributed solutions and integrate with non-Java code. Mule provides the MIF container environment. MIF extends the Mule interface to make component and pipeline construction easier and to create an encapsulation device for component creation. The MIF interface is agnostic of the underlying Java messaging platform. This allows deployments to configure MIF applications using technologies that meet individual quality-of-service requirements.

关键词： Containers

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Understanding the binding of the same ligand to GPCRs of different families

Understanding the binding of the same ligand to GPCRs of dif...

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2021 IEEE International Conference on bioinformatics and Biomedicine, BIBM 2021

作者： Dankwah, Kwabena Owusu Mohl, Jonathon E Begum, Khodeza Leung, Ming-Ying The University of Texas at El Paso Computational Science Program El Paso United States The University of Texas at El Paso Bioinformatics Program Computational Science Program Dept. of Mathematical Sciences El Paso United States The University of Texas at El Paso Bioinformatics Program Border Biomedical Research Center El Paso United States

ISBN: (纸本)9781665401265

G protein-coupled receptors (GPCRs) are the largest class of cell-surface receptor proteins with important functions in signal transduction and often serve as therapeutic drug targets. With the rapidly growing public data on three dimensional (3D) structures of GPCRs and GPCR-ligand interactions, computational prediction of GPCR ligand binding becomes a convincing option to high throughput screening and other experimental approaches during the beginning phases of ligand discovery. Such predictions are cost-efficient and can be important aides for planning wet lab experiments to help elucidate signaling pathways and expedite drug discovery. There are existing computational tools for GPCR ligand binding prediction using various sequence and structural derived features. However, these methods have been typically tested on specific families of GPCRs and none has focused on features that characterize binding of a single ligand to multiple GPCR families. In this work, we set out to uncover and understand the binding of the same ligand to multiple GPCRs of different families. As expected only a few GPCRs share a conserved sequence motif. We observed local 3D structural similarities and local sequence similarities. We also observed that the GPCRs within the same family share similar binding pockets for the ligand. Molecular docking revealed that a ligand can bind to GPCRs of different families with different poses but similar conformations. Finally, the ligands bind to similar pockets with similar electrostatic and solvation properties and share similar residues. These findings can be exploited to improve protein function inference, drug repurposing and drug toxicity prediction, and accelerate the development of new drugs. © 2021 IEEE.

关键词： Ligands

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Comparative Genomics 1

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丛书名： Methods in Molecular Biology

1000年

作者： Nicholas H. Bergman

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miR-let-7a-2, miR103a-2 and CREB1-TF as therapeutic targets to regulate the transcription of DISC1 and PDE4D in the transcriptional regulation pathway by DISC1/ATF4 complex 4

miR-let-7a-2, miR103a-2 and CREB1-TF as therapeutic targets ...

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4th IEEE International Conference on BioInspired Processing, BIP 2022

作者： Rodriguez, Esteban Jose Rodriguez Mora-Rodriguez, Rodrigo San José Costa Rica University of Costa Rica Master Program of Bioinformatics and System Biology Posgraduate Program Sep San José Costa Rica

ISBN: (纸本)9781665470483

Disrupted In Schizophrenia 1 (DISC1) is considered a multifunctional protein implicated in various signaling pathways with neurological relevant outcomes, with the Disrupted In Schizophrenia 1/Activating Transcription Factor 4 (DISC1/ATF4) transcriptional regulation pathway being a pathway of interest since it regulates Phosphodiesterase 4D (PDE4D) transcription. Alterations in the transcription levels of DISC1 and PDE4D have been implicated in neurodegenerative processes and the identification of therapeutic targets that regulate these processes can be of great help to promote neuroprotective processes. By using a System Biology approach, we created a mathematical model of the transcriptional regulation of the DISC1/ATF4 pathway and using this model we conducted in-silico experiments to identify potential therapeutic targets with robust control on the network. As a result, miR-let-7a-2 is reported as a transcriptional regulator of DISC1 as well as miR103-a2 and CREB1-TF as transcriptional regulators of the PDE4D. These three regulators are identified as in-silico therapeutic targets to promote neuroprotective processes against neurodegenerative mental disorders. © 2022 IEEE.

关键词： Robust control

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Bile acid synthesis impedes tumor-specific T cell responses during liver cancer

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Science (New York, N.Y.) 2025年第6730期387卷 192-201页

作者： Varanasi, Siva Karthik Chen, Dan Liu, Yingluo Johnson, Melissa A. Miller, Cayla M. Ganguly, Souradipta Lande, Kathryn LaPorta, Michael A. Hoffmann, Filipe Araujo Mann, Thomas H. Teneche, Marcos G. Casillas, Eduardo Mangalhara, Kailash C. Mathew, Varsha Sun, Ming Jensen, Isaac J. Farsakoglu, Yagmur Chen, Timothy Parisi, Bianca Deota, Shaunak Havas, Aaron Lee, Jin Chung, H Kay Schietinger, Andrea Panda, Satchidananda Williams, April E. Farber, Donna L. Dhar, Debanjan Adams, Peter D. Feng, Gen-Sheng Shadel, Gerald S. Sundrud, Mark S. Kaech, Susan M. NOMIS Center for Immunobiology and Microbial Pathogenesis Salk Institute for Biological Studies La Jolla CA United States Department of Pathology School of Medicine University of California San Diego La Jolla CA United States Sanford Burnham Prebys Medical Discovery Institute La Jolla CA United States Department of Medicine School of Medicine University of California San Diego CA United States Razavi Newman Integrative Genomics and Bioinformatics Core Facility Salk Institute for Biological Studies La Jolla CA United States Department of Microbiology and Immunology Columbia University Irving Medical Center New York NY USA Department of Surgery Columbia University Irving Medical Center New York NY USA Regulatory Biology Laboratory Salk Institute for Biological Studies La Jolla CA United States Immunology Program Memorial Sloan Kettering Cancer Center New York NY USA Immunology and Microbial Pathogenesis Program Weill Cornell Graduate School of Medical Sciences New York NY USA Parker Institute for Cancer Immunotherapy New York NY USA Department of Microbiology and Immunology Geisel School of Medicine at Dartmouth Hanover NH USA Department of Medicine Geisel School of Medicine at Dartmouth Hanover NH USA Center for Digestive Health Dartmouth Health NH United States Dartmouth Cancer Center Dartmouth Health NH United States

The metabolic landscape of cancer greatly influences antitumor immunity, yet it remains unclear how organ-specific metabolites in the tumor microenvironment influence immunosurveillance. We found that accumulation of primary conjugated and secondary bile acids (BAs) are metabolic features of human hepatocellular carcinoma and experimental liver cancer models. Inhibiting conjugated BA synthesis in hepatocytes through deletion of the BA-conjugating enzyme bile acid-CoA:amino acid N-acyltransferase (BAAT) enhanced tumor-specific T cell responses, reduced tumor growth, and sensitized tumors to anti-programmed cell death protein 1 (anti-PD-1) immunotherapy. Furthermore, different BAs regulated CD8+ T cells differently;primary BAs induced oxidative stress, whereas the secondary BA lithocholic acid inhibited T cell function through endoplasmic reticulum stress, which was countered by ursodeoxycholic acid. We demonstrate that modifying BA synthesis or dietary intake of ursodeoxycholic acid could improve tumor immunotherapy in liver cancer model systems.

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