scholarly journals Identification of Disease-Related 2-Oxoglutarate/Fe (II)-Dependent Oxygenase Based on Reduced Amino Acid Cluster Strategy

2021 ◽  
Vol 9 ◽  
Author(s):  
Jian Zhou ◽  
Suling Bo ◽  
Hao Wang ◽  
Lei Zheng ◽  
Pengfei Liang ◽  
...  
Keyword(s):  
Amino Acid ◽  
Protein Modification ◽  
Catalytic Mechanism ◽  
Feature Representation ◽  
Accurate Identification ◽  
Cluster Strategy ◽  
Representation Scheme ◽  
User Friendly ◽  
Optimal Feature

The 2-oxoglutarate/Fe (II)-dependent (2OG) oxygenase superfamily is mainly responsible for protein modification, nucleic acid repair and/or modification, and fatty acid metabolism and plays important roles in cancer, cardiovascular disease, and other diseases. They are likely to become new targets for the treatment of cancer and other diseases, so the accurate identification of 2OG oxygenases is of great significance. Many computational methods have been proposed to predict functional proteins to compensate for the time-consuming and expensive experimental identification. However, machine learning has not been applied to the study of 2OG oxygenases. In this study, we developed OGFE_RAAC, a prediction model to identify whether a protein is a 2OG oxygenase. To improve the performance of OGFE_RAAC, 673 amino acid reduction alphabets were used to determine the optimal feature representation scheme by recoding the protein sequence. The 10-fold cross-validation test showed that the accuracy of the model in identifying 2OG oxygenases is 91.04%. Besides, the independent dataset results also proved that the model has excellent generalization and robustness. It is expected to become an effective tool for the identification of 2OG oxygenases. With further research, we have also found that the function of 2OG oxygenases may be related to their polarity and hydrophobicity, which will help the follow-up study on the catalytic mechanism of 2OG oxygenases and the way they interact with the substrate. Based on the model we built, a user-friendly web server was established and can be friendly accessed at http://bioinfor.imu.edu.cn/ogferaac.

scholarly journals ANPrAod: Identify Antioxidant Proteins by Fusing Amino Acid Clustering Strategy and N -Peptide Combination

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Qilemuge Xi ◽  
Hao Wang ◽  
Liuxi Yi ◽  
Jian Zhou ◽  
Yuchao Liang ◽  
...  
Keyword(s):  
Amino Acid ◽  
Protein Identification ◽  
Critical Role ◽  
Feature Representation ◽  
New Drugs ◽  
Support Vector ◽  
Accurate Identification ◽  
Promising Tool ◽  
Antioxidant Proteins ◽  
Representation Scheme

Antioxidant proteins perform significant functions in disease control and delaying aging which can prevent free radicals from damaging organisms. Accurate identification of antioxidant proteins has important implications for the development of new drugs and the treatment of related diseases, as they play a critical role in the control or prevention of cancer and aging-related conditions. Since experimental identification techniques are time-consuming and expensive, many computational methods have been proposed to identify antioxidant proteins. Although the accuracy of these methods is acceptable, there are still some challenges. In this study, we developed a computational model called ANPrAod to identify antioxidant proteins based on a support vector machine. In order to eliminate potential redundant features and improve prediction accuracy, 673 amino acid reduction alphabets were calculated by us to find the optimal feature representation scheme. The final model could produce an overall accuracy of 87.53% with the ROC of 0.7266 in five-fold cross-validation, which was better than the existing methods. The results of the independent dataset also demonstrated the excellent robustness and reliability of ANPrAod, which could be a promising tool for antioxidant protein identification and contribute to hypothesis-driven experimental design.

Iterative feature representations improve N4-methylcytosine site prediction

2019 ◽  
Vol 35 (23) ◽  
pp. 4930-4937 ◽  
Author(s):  
Leyi Wei ◽  
Ran Su ◽  
Shasha Luan ◽  
Zhijun Liao ◽  
Balachandran Manavalan ◽  
...  
Keyword(s):  
Feature Space ◽  
Feature Representation ◽  
Supplementary Information ◽  
Accurate Identification ◽  
Feature Representations ◽  
Genome Wide ◽  
A Genome ◽  
Benchmark Datasets ◽  
Sequential Models ◽  
User Friendly

Abstract Motivation Accurate identification of N4-methylcytosine (4mC) modifications in a genome wide can provide insights into their biological functions and mechanisms. Machine learning recently have become effective approaches for computational identification of 4mC sites in genome. Unfortunately, existing methods cannot achieve satisfactory performance, owing to the lack of effective DNA feature representations that are capable to capture the characteristics of 4mC modifications. Results In this work, we developed a new predictor named 4mcPred-IFL, aiming to identify 4mC sites. To represent and capture discriminative features, we proposed an iterative feature representation algorithm that enables to learn informative features from several sequential models in a supervised iterative mode. Our analysis results showed that the feature representations learnt by our algorithm can capture the discriminative distribution characteristics between 4mC sites and non-4mC sites, enlarging the decision margin between the positives and negatives in feature space. Additionally, by evaluating and comparing our predictor with the state-of-the-art predictors on benchmark datasets, we demonstrate that our predictor can identify 4mC sites more accurately. Availability and implementation The user-friendly webserver that implements the proposed 4mcPred-IFL is well established, and is freely accessible at http://server.malab.cn/4mcPred-IFL. Supplementary information Supplementary data are available at Bioinformatics online.

Prediction of Neddylation Sites Using the Composition of k-spaced Amino Acid Pairs and Fuzzy SVM

2020 ◽  
Vol 15 (7) ◽  
pp. 725-731
Author(s):  
Zhe Ju ◽  
Shi-Yun Wang
Keyword(s):  
Amino Acid ◽  
Molecular Mechanisms ◽  
Feature Selection Method ◽  
Class Imbalance ◽  
Support Vector ◽  
Post Translational Modification ◽  
Fuzzy Support Vector Machine ◽  
Accurate Identification ◽  
Isopeptide Bonds ◽  
User Friendly

Introduction: Neddylation is the process of ubiquitin-like protein NEDD8 attaching substrate lysine via isopeptide bonds. As a highly dynamic and reversible post-translational modification, lysine neddylation has been found to be involved in various biological processes and closely associated with many diseases. Objective: The accurate identification of neddylation sites is necessary to elucidate the underlying molecular mechanisms of neddylation. As traditional experimental methods are often expensive and time-consuming, it is imperative to design computational methods to identify neddylation sites. Methods: In this study, a novel predictor named CKSAAP_NeddSite is developed to detect neddylation sites. An effective feature encoding technology, the composition of k-spaced amino acid pairs, is used to encode neddylation sites. And the F-score feature selection method is adopted to remove the redundant features. Moreover, a fuzzy support vector machine algorithm is employed to overcome the class imbalance and noise problem. Results: As illustrated by 10-fold cross-validation, CKSAAP_NeddSite achieves an AUC of 0.9848. Independent tests also show that CKSAAP_NeddSite significantly outperforms existing neddylation sites predictor. Therefore, CKSAAP_NeddSite can be a useful bioinformatics tool for the prediction of neddylation sites. Feature analysis shows that some residues around neddylation sites may play an important role in the prediction. Conclusion: The results of analysis and prediction could offer useful information for elucidating the molecular mechanisms of neddylation. A user-friendly web-server for CKSAAP_NeddSite is established at 123.206.31.171/CKSAAP_NeddSite.

scholarly journals Progress towards reduced-crude protein diets for broiler chickens and sustainable chicken-meat production

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Sonia Yun Liu ◽  
Shemil P. Macelline ◽  
Peter V. Chrystal ◽  
Peter H. Selle
Keyword(s):  
Amino Acids ◽  
Amino Acid ◽  
Broiler Chickens ◽  
Crude Protein ◽  
Plasma Concentrations ◽  
Essential Amino Acids ◽  
Chicken Meat ◽  
Meat Production ◽  
Accurate Identification ◽  
Reduced Crude Protein

AbstractThe prime purpose of this review is to explore the pathways whereby progress towards reduced-crude protein (CP) diets and sustainable chicken-meat production may be best achieved. Reduced-CP broiler diets have the potential to attenuate environmental pollution from nitrogen and ammonia emissions; moreover, they have the capacity to diminish the global chicken-meat industry’s dependence on soybean meal to tangible extents. The variable impacts of reduced-CP broiler diets on apparent amino acid digestibility coefficients are addressed. The more accurate identification of amino acid requirements for broiler chickens offered reduced-CP diets is essential as this would diminish amino acid imbalances and the deamination of surplus amino acids. Deamination of amino acids increases the synthesis and excretion of uric acid for which there is a requirement for glycine, this emphasises the value of so-called “non-essential” amino acids. Starch digestive dynamics and their possible impact of glucose on pancreatic secretions of insulin are discussed, although the functions of insulin in avian species require clarification. Maize is probably a superior feed grain to wheat as the basis of reduced-CP diets; if so, the identification of the underlying reasons for this difference should be instructive. Moderating increases in starch concentrations and condensing dietary starch:protein ratios in reduced-CP diets may prove to be advantageous as expanding ratios appear to be aligned to inferior broiler performance. Threonine is specifically examined because elevated free threonine plasma concentrations in birds offered reduced-CP diets may be indicative of compromised performance. If progress in these directions can be realised, then the prospects of reduced-CP diets contributing to sustainable chicken-meat production are promising.

scholarly journals The methyltransferase METTL9 mediates pervasive 1-methylhistidine modification in mammalian proteomes

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Erna Davydova ◽  
Tadahiro Shimazu ◽  
Maren Kirstin Schuhmacher ◽  
Magnus E. Jakobsson ◽  
Hanneke L. D. M. Willemen ◽  
...  
Keyword(s):  
Amino Acid ◽  
Protein Function ◽  
Crucial Role ◽  
Complex I ◽  
Protein Modification ◽  
Zinc Binding ◽  
Functional Studies ◽  
Mitochondrial Respiratory Complex ◽  
Respiratory Complex I ◽  
Broad Specificity

AbstractPost-translational methylation plays a crucial role in regulating and optimizing protein function. Protein histidine methylation, occurring as the two isomers 1- and 3-methylhistidine (1MH and 3MH), was first reported five decades ago, but remains largely unexplored. Here we report that METTL9 is a broad-specificity methyltransferase that mediates the formation of the majority of 1MH present in mouse and human proteomes. METTL9-catalyzed methylation requires a His-x-His (HxH) motif, where “x” is preferably a small amino acid, allowing METTL9 to methylate a number of HxH-containing proteins, including the immunomodulatory protein S100A9 and the NDUFB3 subunit of mitochondrial respiratory Complex I. Notably, METTL9-mediated methylation enhances respiration via Complex I, and the presence of 1MH in an HxH-containing peptide reduced its zinc binding affinity. Our results establish METTL9-mediated 1MH as a pervasive protein modification, thus setting the stage for further functional studies on protein histidine methylation.

scholarly journals How to Use Online Tools to Generate New Hypotheses for Mammary Gland Biology Research: A Case Study for Wnt7b

2021 ◽  
Author(s):  
Yorick Bernardus Cornelis van de Grift ◽  
Nika Heijmans ◽  
Renée van Amerongen
Keyword(s):  
Mammary Gland ◽  
In Silico ◽  
Online Tools ◽  
Mammary Gland Biology ◽  
User Friendly ◽  
In Silico Analyses ◽  
Biology Research ◽  
Selection Of

AbstractAn increasing number of ‘-omics’ datasets, generated by labs all across the world, are becoming available. They contain a wealth of data that are largely unexplored. Not every scientist, however, will have access to the required resources and expertise to analyze such data from scratch. Fortunately, a growing number of investigators is dedicating their time and effort to the development of user friendly, online applications that allow researchers to use and investigate these datasets. Here, we will illustrate the usefulness of such an approach. Using regulation of Wnt7b expression as an example, we will highlight a selection of accessible tools and resources that are available to researchers in the area of mammary gland biology. We show how they can be used for in silico analyses of gene regulatory mechanisms, resulting in new hypotheses and providing leads for experimental follow up. We also call out to the mammary gland community to join forces in a coordinated effort to generate and share additional tissue-specific ‘-omics’ datasets and thereby expand the in silico toolbox.

Pl@ntwood: A Computer-Assisted Identification Tool for 110 species of amazon trees based on wood Anatomical Features

IAWA Journal ◽  
2011 ◽  
Vol 32 (2) ◽  
pp. 221-232 ◽  
Author(s):  
Carolina Sarmiento ◽  
Pierre Détienne ◽  
Christine Heinz ◽  
Jean-François Molino ◽  
Pierre Grard ◽  
...  
Keyword(s):  
Tree Species ◽  
Tropical Species ◽  
Computer Assisted ◽  
Accurate Identification ◽  
Anatomical Features ◽  
System A ◽  
Microscopic Features ◽  
On Line ◽  
User Friendly ◽  
Identification Tool

Sustainable management and conservation of tropical trees and forests require accurate identification of tree species. Reliable, user-friendly identification tools based on macroscopic morphological features have already been developed for various tree floras. Wood anatomical features provide also a considerable amount of information that can be used for timber traceability, certification and trade control. Yet, this information is still poorly used, and only a handful of experts are able to use it for plant species identification. Here, we present an interactive, user-friendly tool based on vector graphics, illustrating 99 states of 27 wood characters from 110 Amazonian tree species belonging to 34 families. Pl@ntWood is a graphical identification tool based on the IDAO system, a multimedia approach to plant identification. Wood anatomical characters were selected from the IAWA list of microscopic features for hardwood identification, which will enable us to easily extend this work to a larger number of species. A stand-alone application has been developed and an on-line version will be delivered in the near future. Besides allowing non-specialists to identify plants in a user-friendly interface, this system can be used with different purposes such as teaching, conservation, management, and selftraining in the wood anatomy of tropical species.

Implementation of “Epic Healthy Planet” registry for survivorship care coordination.

2021 ◽  
Vol 39 (28_suppl) ◽  
pp. 337-337
Author(s):  
Karen Kinahan ◽  
Bijal Desai ◽  
Michele Volpentesta ◽  
Margo Klein ◽  
Melissa Duffy ◽  
...  
Keyword(s):  
Medical Oncology ◽  
Discrete Data ◽  
Mandatory Reporting ◽  
Survivorship Care ◽  
Management Tools ◽  
Noticeable Increase ◽  
Episode Of Care ◽  
Data Points ◽  
User Friendly

337 Background: The evolving Commission on Cancer (CoC) reporting mandate and institution’s growing survivorship program led to identifying the need for systematic tracking of survivorship patients, surveillance tests, return appointments and referrals placed. Our aim was to develop an electronic medical record (EMR) integrated registry utilizing discrete data fields to assist our team in tracking key elements of high-quality survivorship care. Methods: Stakeholders from our survivorship team (APP/RN), medical oncology, psychology, research, operations and IT analytics reached consensus on essential discrete EMR fields to be included in the registry. For implementation we utilized the EPIC module, “Healthy Planet”, where patients enter the registry by initiating an “Episode of Care” at their initial survivorship visit. SmartForm fields create unique discrete patient data points identified by the stakeholders. Results: The following domains were identified as important elements of care that require tracking in a dedicated survivorship program. The registry domains populate from two sources: 1) currently existing EMR data fields, 2) domains with no currently discrete data (e.g. lymphedema, peripheral neuropathy) were captured in the developed SmartForm (see Table). From January 1, 2019 to June 1, 2021, 778 patients were entered into the registry. Since September 4, 2020, 112 patient follow-up appointment reminders were sent via EMR which has led to a noticeable increase in return appointments. SmartForm data fields are being amended as additional malignancy types are added to our survivorship program. Conclusions: The utilization of Healthy Planet is an effective and user-friendly way to track survivorship return appointments, remind providers of diagnostic tests that are due, and track referrals for CoC reporting. As the numbers of cancer survivors continues to increase, systematic population management tools are essential to ensure adherence to survivorship guideline recommendations, follow-up care and mandatory reporting.[Table: see text]

Advantages and Challenges of Using Breast Biopsy Markers

2021 ◽  
Author(s):  
Taghreed I Alshafeiy ◽  
Alison Matich ◽  
Carrie M Rochman ◽  
Jennifer A Harvey
Keyword(s):  
Breast Biopsy ◽  
Percutaneous Biopsy ◽  
Standard Of Care ◽  
Benign Lesions ◽  
Accurate Identification ◽  
Biopsy Tissue ◽  
Local Practices ◽  
Frequency Of Use ◽  
Lesion Localization

Abstract Percutaneous image-guided biopsy procedures are the standard of care for histologic assessment of suspicious breast lesions. Post-biopsy tissue markers (clips) optimize patient management by allowing for assessment on follow-up imaging and precise lesion localization. Markers are used to ensure accurate correlation between imaging modalities, guide preoperative localization for malignant and high-risk lesions, and facilitate accurate identification of benign lesions at follow-up. Local practices differ widely, and there are no data detailing the exact frequency of use of clips for different breast biopsies. There are many indications for biopsy marker deployment, and some difficulties may be encountered after placement. The placement of biopsy markers has many advantages and few disadvantages, such that deployment should be routinely used after percutaneous biopsy procedures with rare exception.

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