scholarly journals iMRM: a platform for simultaneously identifying multiple kinds of RNA modifications

2020 ◽  
Vol 36 (11) ◽  
pp. 3336-3342 ◽  
Author(s):  
Kewei Liu ◽  
Wei Chen
Keyword(s):  
Computational Methods ◽  
Homo Sapiens ◽  
Supplementary Information ◽  
Rna Modifications ◽  
Feature Selection Technique ◽  
Jackknife Test ◽  
The Past ◽  
User Friendly ◽  
Fold Cross Validation ◽  
Command Line Version

Abstract Motivation RNA modifications play critical roles in a series of cellular and developmental processes. Knowledge about the distributions of RNA modifications in the transcriptomes will provide clues to revealing their functions. Since experimental methods are time consuming and laborious for detecting RNA modifications, computational methods have been proposed for this aim in the past five years. However, there are some drawbacks for both experimental and computational methods in simultaneously identifying modifications occurred on different nucleotides. Results To address such a challenge, in this article, we developed a new predictor called iMRM, which is able to simultaneously identify m6A, m5C, m1A, ψ and A-to-I modifications in Homo sapiens, Mus musculus and Saccharomyces cerevisiae. In iMRM, the feature selection technique was used to pick out the optimal features. The results from both 10-fold cross-validation and jackknife test demonstrated that the performance of iMRM is superior to existing methods for identifying RNA modifications. Availability and implementation A user-friendly web server for iMRM was established at http://www.bioml.cn/XG_iRNA/home. The off-line command-line version is available at https://github.com/liukeweiaway/iMRM. Contact [email protected] Supplementary information Supplementary data are available at Bioinformatics online.

iCarPS: a computational tool for identifying protein carbonylation sites by novel encoded features

2020 ◽  
Author(s):  
Dan Zhang ◽  
Zhao-Chun Xu ◽  
Wei Su ◽  
Yu-He Yang ◽  
Hao Lv ◽  
...  
Keyword(s):  
Protein Carbonylation ◽  
Supplementary Information ◽  
Sequence Information ◽  
Biological Processes ◽  
Feature Selection Technique ◽  
Post Translational Modifications ◽  
Proposed Model ◽  
Feature Encoding ◽  
Feature Encoding Scheme ◽  
User Friendly

Abstract Motivation Protein carbonylation is one of the most important oxidative stress-induced post-translational modifications, which is generally characterized as stability, irreversibility and relative early formation. It plays a significant role in orchestrating various biological processes and has been already demonstrated to be related to many diseases. However, the experimental technologies for carbonylation sites identification are not only costly and time consuming, but also unable of processing a large number of proteins at a time. Thus, rapidly and effectively identifying carbonylation sites by computational methods will provide key clues for the analysis of occurrence and development of diseases. Results In this study, we developed a predictor called iCarPS to identify carbonylation sites based on sequence information. A novel feature encoding scheme called residues conical coordinates combined with their physicochemical properties was proposed to formulate carbonylated protein and non-carbonylated protein samples. To remove potential redundant features and improve the prediction performance, a feature selection technique was used. The accuracy and robustness of iCarPS were proved by experiments on training and independent datasets. Comparison with other published methods demonstrated that the proposed method is powerful and could provide powerful performance for carbonylation sites identification. Availability and implementation Based on the proposed model, a user-friendly webserver and a software package were constructed, which can be freely accessed at http://lin-group.cn/server/iCarPS. Supplementary information Supplementary data are available at Bioinformatics online.

i6mA-Pred: identifying DNA N6-methyladenine sites in the rice genome

2019 ◽  
Vol 35 (16) ◽  
pp. 2796-2800 ◽  
Author(s):  
Wei Chen ◽  
Hao Lv ◽  
Fulei Nie ◽  
Hao Lin
Keyword(s):  
Dna Sequences ◽  
Rice Genome ◽  
Chemical Properties ◽  
Computational Method ◽  
Accurate Identification ◽  
Feature Selection Technique ◽  
Jackknife Test ◽  
Genome Wide ◽  
Wide Range ◽  
User Friendly

Abstract Motivation DNA N6-methyladenine (6mA) is associated with a wide range of biological processes. Since the distribution of 6mA site in the genome is non-random, accurate identification of 6mA sites is crucial for understanding its biological functions. Although experimental methods have been proposed for this regard, they are still cost-ineffective for detecting 6mA site in genome-wide scope. Therefore, it is desirable to develop computational methods to facilitate the identification of 6mA site. Results In this study, a computational method called i6mA-Pred was developed to identify 6mA sites in the rice genome, in which the optimal nucleotide chemical properties obtained by the using feature selection technique were used to encode the DNA sequences. It was observed that the i6mA-Pred yielded an accuracy of 83.13% in the jackknife test. Meanwhile, the performance of i6mA-Pred was also superior to other methods. Availability and implementation A user-friendly web-server, i6mA-Pred is freely accessible at http://lin-group.cn/server/i6mA-Pred.

Comparison and Analysis of Computational Methods for Identifying N6 - methyladenosine Sites in Saccharomyces Cerevisiae

2020 ◽  
Vol 26 ◽  
Author(s):  
Pengmian Feng ◽  
Lijing Feng ◽  
Chaohui Tang
Keyword(s):  
Saccharomyces Cerevisiae ◽  
Computational Methods ◽  
Computational Analysis ◽  
Computational Prediction ◽  
Experimental Methods ◽  
Biological Processes ◽  
Biological Functions ◽  
Precise Location ◽  
Future Directions ◽  
The Past

Background and Purpose: N 6 -methyladenosine (m6A) plays critical roles in a broad set of biological processes. Knowledge about the precise location of m6A site in the transcriptome is vital for deciphering its biological functions. Although experimental techniques have made substantial contributions to identify m6A, they are still labor intensive and time consuming. As good complements to experimental methods, in the past few years, a series of computational approaches have been proposed to identify m6A sites. Methods: In order to facilitate researchers to select appropriate methods for identifying m6A sites, it is necessary to give a comprehensive review and comparison on existing methods. Results: Since researches on m6A in Saccharomyces cerevisiae are relatively clear, in this review, we summarized recent progresses on computational prediction of m6A sites in S. cerevisiae and assessed the performance of existing computational methods. Finally, future directions of computationally identifying m6A sites were presented. Conclusion: Taken together, we anticipate that this review will provide important guides for computational analysis of m 6A modifications.

Introduction

2018 ◽  
Author(s):  
Gianfranco Pacchioni
Keyword(s):  
Industrial Revolution ◽  
Homo Sapiens ◽  
Modern Society ◽  
Full Time ◽  
Human Race ◽  
Hunter Gatherers ◽  
The Past ◽  
The World ◽  
The Universe ◽  
Radical Transformation

About 10,000 years ago, at the beginning of the agriculturalrevolution, on the whole earth lived between 5 and 8 million hunter-gatherers, all belonging to the Homo sapiens species. Five thousand years later, freed from the primary needs for survival, some belonging to that species enjoyed the privilege of devoting themselves to philosophical speculation and the search for transcendental truths. It was only in the past two hundred years, however, with the advent of the Industrial Revolution, that reaping nature’s secrets and answering fundamental questions posed by the Universe have become for many full-time activities, on the way to becoming a real profession. Today the number of scientists across the globe has reached and exceeded 10 million, that is, more than the whole human race 10,000 years ago. If growth continues at the current rate, in 2050 we will have 35 million people committed full-time to scientific research. With what consequences, it remains to be understood. For almost forty years I myself have been concerned with science in a continuing, direct, and passionate way. Today I perceive, along with many colleagues, especially of my generation, that things are evolving and have changed deeply, in ways unimaginable until a few years ago and, in some respects, not without danger. What has happened in the world of science in recent decades is more than likely a mirror of a similar and equally radical transformation taking place in modern society, particularly with the advent ...

“So Quick Bright Things Come to Confusion”

1987 ◽  
Vol 13 (2-3) ◽  
pp. 169-187
Author(s):  
Alexander Morgan Capron
Keyword(s):  
Homo Sapiens ◽  
Care Delivery ◽  
Well Being ◽  
Workplace Safety ◽  
Selective Abortion ◽  
Self Identity ◽  
The Past ◽  
Adverse Impacts ◽  
The Rich ◽  
Insurance Discrimination

In the past several decades, the problems facing those of us who labor in the vineyards of health policy and ethics have been the problems of success — first medicine's and then, though to a lesser extent, our own. By this I mean that it has been the remarkable fruits of biomedicine, from research to health care delivery, that have produced the rich harvest of ethical, social and legal issues that have drawn our, and society's, attention.In the basic science laboratory, scientists have developed means to splice pieces of DNA together, raising questions from workplace safety to the reengineering of homo sapiens. Of more immediate concern, tests for genetic susceptibility to disease in one's self and one's offspring have been developed, thereby generating questions about employment and insurance discrimination, selective abortion, and adverse impacts on self-identity and well-being.

scholarly journals Ribo-ODDR: Oligo design pipeline for experiment-specific rRNA depletion in ribo-seq

2021 ◽  
Author(s):  
Ferhat Alkan ◽  
Joana Silva ◽  
Eric Pintó Barberà ◽  
William J Faller
Keyword(s):  
Ribosome Profiling ◽  
Supplementary Information ◽  
Experimental Conditions ◽  
Computational Framework ◽  
Rna Translation ◽  
Rrna Depletion ◽  
Selection For ◽  
Nucleotide Resolution ◽  
User Friendly ◽  
Oligo Design

Abstract Motivation Ribosome Profiling (Ribo-seq) has revolutionized the study of RNA translation by providing information on ribosome positions across all translated RNAs with nucleotide-resolution. Yet several technical limitations restrict the sequencing depth of such experiments, the most common of which is the overabundance of rRNA fragments. Various strategies can be employed to tackle this issue, including the use of commercial rRNA depletion kits. However, as they are designed for more standardized RNAseq experiments, they may perform suboptimally in Ribo-seq. In order to overcome this, it is possible to use custom biotinylated oligos complementary to the most abundant rRNA fragments, however currently no computational framework exists to aid the design of optimal oligos. Results Here, we first show that a major confounding issue is that the rRNA fragments generated via Ribo-seq vary significantly with differing experimental conditions, suggesting that a “one-size-fits-all” approach may be inefficient. Therefore we developed Ribo-ODDR, an oligo design pipeline integrated with a user-friendly interface that assists in oligo selection for efficient experiment-specific rRNA depletion. Ribo-ODDR uses preliminary data to identify the most abundant rRNA fragments, and calculates the rRNA depletion efficiency of potential oligos. We experimentally show that Ribo-ODDR designed oligos outperform commercially available kits and lead to a significant increase in rRNA depletion in Ribo-seq. Availability Ribo-ODDR is freely accessible at https://github.com/fallerlab/Ribo-ODDR Supplementary information Supplementary data are available at Bioinformatics online.

CPVA: a web-based metabolomic tool for chromatographic peak visualization and annotation

2020 ◽  
Vol 36 (12) ◽  
pp. 3913-3915
Author(s):  
Hemi Luan ◽  
Xingen Jiang ◽  
Fenfen Ji ◽  
Zhangzhang Lan ◽  
Zongwei Cai ◽  
...  
Keyword(s):  
False Positive ◽  
Supplementary Information ◽  
Liquid Chromatography Mass Spectrometry ◽  
Targeted Metabolomics ◽  
Metabolomics Data ◽  
Web Based ◽  
Tremendous Amount ◽  
Chromatographic Peaks ◽  
User Friendly

Abstract Motivation Liquid chromatography–mass spectrometry-based non-targeted metabolomics is routinely performed to qualitatively and quantitatively analyze a tremendous amount of metabolite signals in complex biological samples. However, false-positive peaks in the datasets are commonly detected as metabolite signals by using many popular software, resulting in non-reliable measurement. Results To reduce false-positive calling, we developed an interactive web tool, termed CPVA, for visualization and accurate annotation of the detected peaks in non-targeted metabolomics data. We used a chromatogram-centric strategy to unfold the characteristics of chromatographic peaks through visualization of peak morphology metrics, with additional functions to annotate adducts, isotopes and contaminants. CPVA is a free, user-friendly tool to help users to identify peak background noises and contaminants, resulting in decrease of false-positive or redundant peak calling, thereby improving the data quality of non-targeted metabolomics studies. Availability and implementation The CPVA is freely available at http://cpva.eastus.cloudapp.azure.com. Source code and installation instructions are available on GitHub: https://github.com/13479776/cpva. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Dental tissue proportions in fossil orangutans from mainland Asia and Indonesia

2011 ◽  
Vol 1 (1) ◽  
pp. e1 ◽  
Author(s):  
Tanya M. Smith ◽  
Anne-Marie Bacon ◽  
Fabrice Demeter ◽  
Ottmar Kullmer ◽  
Kim Thuy Nguyen ◽  
...  
Keyword(s):  
Fossil Record ◽  
Homo Sapiens ◽  
Homo Erectus ◽  
Dental Tissue ◽  
Developmental Constraints ◽  
Enamel Thickness ◽  
Selective Pressures ◽  
The Past ◽  
Geometric Scaling ◽  
Dental Reduction

Orangutans (Pongo) are the only great ape genus with a substantial Pleistocene and Holocene fossil record, demonstrating a much larger geographic range than extant populations. In addition to having an extensive fossil record, Pongo shows several convergent morphological similarities with Homo, including a trend of dental reduction during the past million years. While studies have documented variation in dental tissue proportions among species of Homo, little is known about variation in enamel thickness within fossil orangutans. Here we assess dental tissue proportions, including conventional enamel thickness indices, in a large sample of fossil orangutan postcanine teeth from mainland Asia and Indonesia. We find few differences between regions, except for significantly lower average enamel thickness (AET) values in Indonesian mandibular first molars. Differences between fossil and extant orangutans are more marked, with fossil Pongo showing higher AET in most postcanine teeth. These differences are significant for maxillary and mandibular first molars. Fossil orangutans show higher AET than extant Pongo due to greater enamel cap areas, which exceed increases in enamel-dentine junction length (due to geometric scaling of areas and lengths for the AET index calculation). We also find greater dentine areas in fossil orangutans, but relative enamel thickness indices do not differ between fossil and extant taxa. When changes in dental tissue proportions between fossil and extant orangutans are compared with fossil and recent Homo sapiens, Pongo appears to show isometric reduction in enamel and dentine, while crown reduction in H. sapiens appears to be due to preferential loss of dentine. Disparate selective pressures or developmental constraints may underlie these patterns. Finally, the finding of moderately thick molar enamel in fossil orangutans may represent an additional convergent dental similarity with Homo erectus, complicating attempts to distinguish these taxa in mixed Asian faunas. 

MetaADEDB 2.0: a comprehensive database on adverse drug events

2020 ◽  
Author(s):  
Zhuohang Yu ◽  
Zengrui Wu ◽  
Weihua Li ◽  
Guixia Liu ◽  
Yun Tang
Keyword(s):  
Safety Assessment ◽  
Adverse Drug Events ◽  
Adverse Event Reporting System ◽  
Adverse Event Reporting ◽  
Supplementary Information ◽  
Online Database ◽  
Web Interface ◽  
Drug Discovery And Development ◽  
Comprehensive Information ◽  
User Friendly

Abstract Summary MetaADEDB is an online database we developed to integrate comprehensive information on adverse drug events (ADEs). The first version of MetaADEDB was released in 2013 and has been widely used by researchers. However, it has not been updated for more than seven years. Here, we reported its second version by collecting more and newer data from the U.S. FDA Adverse Event Reporting System (FAERS) and Canada Vigilance Adverse Reaction Online Database, in addition to the original three sources. The new version consists of 744 709 drug–ADE associations between 8498 drugs and 13 193 ADEs, which has an over 40% increase in drug–ADE associations compared to the previous version. Meanwhile, we developed a new and user-friendly web interface for data search and analysis. We hope that MetaADEDB 2.0 could provide a useful tool for drug safety assessment and related studies in drug discovery and development. Availability and implementation The database is freely available at: http://lmmd.ecust.edu.cn/metaadedb/. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals PathScore: a web tool for identifying altered pathways in cancer data

2016 ◽  
Author(s):  
Stephen G. Gaffney ◽  
Jeffrey P. Townsend
Keyword(s):  
Web Application ◽  
Somatic Mutations ◽  
Supplementary Information ◽  
Web Tool ◽  
Cancer Data ◽  
Link Type ◽  
Novel Approach ◽  
Supplementary Material ◽  
User Friendly ◽  
Pathway Effect

ABSTRACTSummaryPathScore quantifies the level of enrichment of somatic mutations within curated pathways, applying a novel approach that identifies pathways enriched across patients. The application provides several user-friendly, interactive graphic interfaces for data exploration, including tools for comparing pathway effect sizes, significance, gene-set overlap and enrichment differences between projects.Availability and ImplementationWeb application available at pathscore.publichealth.yale.edu. Site implemented in Python and MySQL, with all major browsers supported. Source code available at github.com/sggaffney/pathscore with a GPLv3 [email protected] InformationAdditional documentation can be found at http://pathscore.publichealth.yale.edu/faq.

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