scholarly journals A Database and Evaluation for Classification of RNA Molecules Using Graph Methods

2019 ◽  
pp. 78-87
Author(s):  
Enes Algul ◽  
Richard C. Wilson
Keyword(s):  
Rna Molecules

SVM Model for Prediction and Classification of Drosophila Based on Nucleotide Composition

2011 ◽  
Vol 403-408 ◽  
pp. 2027-2032
Author(s):  
Ananjay Singh ◽  
Kireet Joshi ◽  
Bhasker Pant
Keyword(s):  
Large Family ◽  
Nucleotide Composition ◽  
Regulate Gene Expression ◽  
Rna Molecules ◽  
Svm Model ◽  
Wet Lab ◽  
Non Coding Rnas ◽  
Validation Technique ◽  
Fold Cross Validation

MicroRNAs (miRNA) are single-stranded RNA molecules of about 21–23 nucleotides in length. MicroRNAs(miRNAs) constitute a large family of non coding RNAs that function to regulate gene expression. Till today wet lab experiments have been used to classify the miRNA of plants and animals. The wet lab techniques are highly expensive, labour intensive and time consuming. Thus there arises a need for computational approach for classification of plants and animal miRNA. These computational approaches are fast and economical as compared to wet lab techniques. In this paper an attempt has been made for the classification of Drosophila and its subclasses.The overall prediction accuracy of SVM modules based on mono nucleotide composition was 83.12% respectively. The accuracy of all the modules was evaluated using a 10-fold cross-validation technique.

scholarly journals Using balances to engineer features for the classification of health biomarkers: a new approach to balance selection

2019 ◽  
Author(s):  
Thomas P. Quinn ◽  
Ionas Erb
Keyword(s):  
Simple Procedure ◽  
Cost Effective ◽  
Turn Of The Century ◽  
Molecular Profile ◽  
Rna Molecules ◽  
Technological Advances ◽  
Effective Manner ◽  
Balance Analysis ◽  
Active Research

AbstractSince the turn of the century, technological advances have made it possible to obtain a molecular profile of any tissue in a cost-effective manner. Among these advances include sophisticated high-throughput assays that measure the relative abundance of microorganisms, RNA molecules, and metabolites. While these data are most often collected to gain new insights into biological systems, they can also be used as biomarkers to create clinically useful diagnostic classifiers. How best to classify high-dimensional “-omics” data remains an area of active research. However, few explicitly model the relative nature of these data, and instead rely on cumbersome normalizations which often invoke untestable assumptions. This report (a) emphasizes the relative nature of health biomarkers, (b) discusses the literature surrounding the classification of relative data, and (c) benchmarks how different transformations perform across multiple biomarker types. In doing so, this report explores how one could use balances to engineer features prior to classification, and proposes a simple procedure, called discriminative balance analysis, to select discriminative 2- and 3-part balances.

scholarly journals miRNAFinder: A Comprehensive Web Resource for Plant Pre-microRNA Classification

2021 ◽  
Author(s):  
Sandali Lokuge ◽  
Shyaman Jayasundara ◽  
Puwasuru Ihalagedara ◽  
Damayanthi Herath ◽  
Indika Kahanda
Keyword(s):  
Mature Mirnas ◽  
Structural Features ◽  
Test Machine ◽  
Rna Molecules ◽  
Web Resource ◽  
Mirna Identification ◽  
Overlapping Data ◽  
Non Coding Rna ◽  
Precursor Mirnas

microRNAs (miRNAs) are known as one of the small non-coding RNA molecules, which control the expressions of genes at the RNA level. They typically range 20-24 nucleotides in length and can be found in the plant and animal kingdoms and in some viruses. Computational approaches have overcome the limitations in the experimental methods and have performed well in identifying miRNAs. Compared to mature miRNAs, precursor miRNAs (pre-miRNAs) are long and have a hairpin loop structure with structural features. Therefore, most in-silico tools are implemented for the pre-miRNAs identification. This study presents a multilayer perceptron (MLP) based classifier implemented using 180 features under sequential, structural, and thermodynamic feature categories for plant pre-miRNA identification. This classifier has a 92% accuracy, 94% specificity, and 90% sensitivity. We have further tested this model with other small non-coding RNA types and obtained 78% accuracy. Furthermore, we introduce a novel dataset to train and test machine learning models, addressing the overlapping data issue in positive training and testing datasets presented in PlantMiRNAPred, a study done by Xuan et al. for the classification of real and pseudo plant pre-miRNAs. The new dataset and the classifier are deployed on a web server which is freely accessible via http://mirnafinder.shyaman.me/.

Note on the spectral classification of carbon stars in the photographic infrared region

1966 ◽  
Vol 24 ◽  
pp. 21-23
Author(s):  
Y. Fujita
Keyword(s):  
Infrared Region ◽  
Spectral Classification ◽  
Carbon Stars

We have investigated the spectrograms (dispersion: 8Å/mm) in the photographic infrared region fromλ7500 toλ9000 of some carbon stars obtained by the coudé spectrograph of the 74-inch reflector attached to the Okayama Astrophysical Observatory. The names of the stars investigated are listed in Table 1.

Diagnostic Value of Electron Microscopy in Soft Tissue Tumors

1970 ◽  
Vol 28 ◽  
pp. 220-221
Author(s):  
Gerald Fine ◽  
Azorides R. Morales
Keyword(s):  
Cardiac Myxoma ◽  
Osteogenic Sarcoma ◽  
Diagnostic Value ◽  
Soft Tissue Tumors ◽  
Amelanotic Melanoma ◽  
Growth Patterns ◽  
Light Microscopic Level ◽  
Mesenchymal Tumors ◽  
Good Agreement

For years the separation of carcinoma and sarcoma and the subclassification of sarcomas has been based on the appearance of the tumor cells and their microscopic growth pattern and information derived from certain histochemical and special stains. Although this method of study has produced good agreement among pathologists in the separation of carcinoma from sarcoma, it has given less uniform results in the subclassification of sarcomas. There remain examples of neoplasms of different histogenesis, the classification of which is questionable because of similar cytologic and growth patterns at the light microscopic level; i.e. amelanotic melanoma versus carcinoma and occasionally sarcoma, sarcomas with an epithelial pattern of growth simulating carcinoma, histologically similar mesenchymal tumors of different histogenesis (histiocytoma versus rhabdomyosarcoma, lytic osteogenic sarcoma versus rhabdomyosarcoma), and myxomatous mesenchymal tumors of diverse histogenesis (myxoid rhabdo and liposarcomas, cardiac myxoma, myxoid neurofibroma, etc.)

Ultrastructure of mesotheliomas

1984 ◽  
Vol 42 ◽  
pp. 98-101
Author(s):  
Irving Dardick
Keyword(s):  
Electron Microscopy ◽  
Latent Period ◽  
Spindle Cell ◽  
Spindle Cell Sarcoma ◽  
Metastatic Adenocarcinoma ◽  
Cell Sarcoma ◽  
Cytological Features ◽  
Industrial Use ◽  
Degree Of Differentiation

With the extensive industrial use of asbestos in this century and the long latent period (20-50 years) between exposure and tumor presentation, the incidence of malignant mesothelioma is now increasing. Thus, surgical pathologists are more frequently faced with the dilemma of differentiating mesothelioma from metastatic adenocarcinoma and spindle-cell sarcoma involving serosal surfaces. Electron microscopy is amodality useful in clarifying this problem.In utilizing ultrastructural features in the diagnosis of mesothelioma, it is essential to appreciate that the classification of this tumor reflects a variety of morphologic forms of differing biologic behavior (Table 1). Furthermore, with the variable histology and degree of differentiation in mesotheliomas it might be expected that the ultrastructure of such tumors also reflects a range of cytological features. Such is the case.

Electron Microscopy of the Nucleic Acid of Mouse Mammary Tumor Virus

1968 ◽  
Vol 26 ◽  
pp. 22-23
Author(s):  
N. H. Sarkar ◽  
Dan H. Moore
Keyword(s):  
Mammary Tumor ◽  
Mouse Mammary Tumor Virus ◽  
Ammonium Acetate ◽  
Dry Weight ◽  
Mouse Tumor ◽  
Mammary Tumor Virus ◽  
Rna Molecules ◽  
Mouse Mammary Tumor ◽  
Tumor Virus ◽  
The Subject

Mouse mammary tumor virus (MTV) is believed to contain about 0.8% single stranded ribonucleic acid (RNA). This value of RNA content was estimated on a dry weight basis. The subject of this report is an attempt to visualize the RNA molecules of MTV particles.MTV particles were isolated from RIII mouse (tumor incidence approximately 80%) milk according to the method described by Lyons and Moore. Purified virions from 5 ml of milk were finally suspended in 0.2 ml of PBS, pH 7.4 and was mixed with an equal volume of pronase (5 mg/ml). This mixture was incubated at 37°C for an hour. RNA was extracted three times using freshly prepared cold phenol. It was then treated three times with cold ethyl ether to remove any trace of phenol. The RNA thus extracted was divided into two parts. One part was diluted four fold with 8M urea to avoid aggregation of the molecules. The other part was left untreated. Both samples were then mixed with an equal volume of 1M ammonium acetate, adjusted to pH 8.0 with NH3 containing chymotrypsin at a concentration of 0.01%.

Electron Microscope Study of RNA's of Paramyxoviruses

1972 ◽  
Vol 30 ◽  
pp. 196-197
Author(s):  
Ruchama Baum ◽  
J.T. Seto
Keyword(s):  
Electron Microscopy ◽  
Electron Microscope ◽  
Electron Microscope Study ◽  
Sendai Virus ◽  
Sodium Dodecyl ◽  
Rna Molecules ◽  
Virus Particles ◽  
Molecular Weights ◽  
Length Measurements

The ribonucleic acid (RNA) of paramyxoviruses has been characterized by biochemical and physiochemical methods. However, paramyxovirus RNA molecules have not been studied by electron microscopy. The molecular weights of these single-stranded viral RNA molecules are not known as yet. Since electron microscopy has been found to be useful for the characterization of single-stranded RNA, this investigation was initiated to examine the morphology and length measurements of paramyxovirus RNA's.Sendai virus Z strain and Newcastle disease virus (NDV), Milano strain, were used. For these studies it was necessary to develop a method of extracting RNA molecules from purified virus particles. Highly purified Sendai virus was treated with pronase (300 μg/ml) at 37°C for 30 minutes and the RNA extracted by the sodium dodecyl sulfate (SDS)-phenol procedure.

Interpreting HVEM of muscle-cell impulse networks

1992 ◽  
Vol 50 (1) ◽  
pp. 126-127
Author(s):  
Paul DeCosta ◽  
Kyugon Cho ◽  
Stephen Shemlon ◽  
Heesung Jun ◽  
Stanley M. Dunn
Keyword(s):  
Structural Analysis ◽  
Muscle Cell ◽  
Electron Micrographs ◽  
Relative Size ◽  
Automatic Classification ◽  
Nerve Fibers ◽  
Analysis Algorithm ◽  
Structural Networks

Introduction: The analysis and interpretation of electron micrographs of cells and tissues, often requires the accurate extraction of structural networks, which either provide immediate 2D or 3D information, or from which the desired information can be inferred. The images of these structures contain lines and/or curves whose orientation, lengths, and intersections characterize the overall network.Some examples exist of studies that have been done in the analysis of networks of natural structures. In, Sebok and Roemer determine the complexity of nerve structures in an EM formed slide. Here the number of nodes that exist in the image describes how dense nerve fibers are in a particular region of the skin. Hildith proposes a network structural analysis algorithm for the automatic classification of chromosome spreads (type, relative size and orientation).

Dual stain kit for the microscopic gram classification of ocular infection bacteria

1993 ◽  
Vol 51 ◽  
pp. 248-249
Author(s):  
Jacob S. Hanker ◽  
Dale N. Holdren ◽  
Kenneth L. Cohen ◽  
Beverly L. Giammara
Keyword(s):  
Contact Lenses ◽  
Ocular Infection ◽  
Gram Negative Bacteria ◽  
Gram Negative ◽  
Gram Staining ◽  
Ocular Infections ◽  
Different Types ◽  
Culture Positive ◽  
Increased Susceptibility

Keratitis and conjunctivitis (infections of the cornea or conjunctiva) are ocular infections caused by various bacteria, fungi, viruses or parasites; bacteria, however, are usually prominent. Systemic conditions such as alcoholism, diabetes, debilitating disease, AIDS and immunosuppressive therapy can lead to increased susceptibility but trauma and contact lens use are very important factors. Gram-negative bacteria are most frequently cultured in these situations and Pseudomonas aeruginosa is most usually isolated from culture-positive ulcers of patients using contact lenses. Smears for staining can be obtained with a special swab or spatula and Gram staining frequently guides choice of a therapeutic rinse prior to the report of the culture results upon which specific antibiotic therapy is based. In some cases staining of the direct smear may be diagnostic in situations where the culture will not grow. In these cases different types of stains occasionally assist in guiding therapy.

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