Interdisciplinary Sciences, Computational Life Sciences This is an RSS file. You can use it to subscribe to this data in your favourite RSS reader or to display this data on your own website or blog.

Automatic Detection of Genetics and Genomics of Eye Disease Using Deep Assimilation Learning Algorithm
AbstractDiabetic retinopathy (DR) is one of the most prevalent genetic diseases in human and it is caused by damage to the blood vessels in the eye retina. If it is undetected and untreated at right time, it can lead to vision loss. There are many medical imaging and processing technologies to improve the diagnostic process of DR to overcome the lack of human experts. In the existing image processing methods, there are issues such as lack of noise removal, improper clustering segmentation and less classification accuracy. This can be accomplished by automatic diagnosis of DR using advanced image processing method. The cott...
Source: Interdisciplinary Sciences, Computational Life Sciences - January 4, 2021 Category: Bioinformatics Source Type: research

A machine learning-based framework for diagnosis of COVID-19 from chest X-ray images
AbstractCorona virus disease (COVID-19) acknowledged as a pandemic by the WHO and mankind all over the world is vulnerable to this virus. Alternative tools are needed that can help in diagnosis of the coronavirus. Researchers of this article investigated the potential of machine learning methods for automatic diagnosis of corona virus with high accuracy from X-ray images. Two most commonly used classifiers were selected: logistic  regression (LR) and convolutional neural networks (CNN). The main reason was to make the system fast and efficient. Moreover, a dimensionality reduction approach was also investigated based on p...
Source: Interdisciplinary Sciences, Computational Life Sciences - January 2, 2021 Category: Bioinformatics Source Type: research

Ultra-Fast Computation of Excited-States Spectra for Large Systems: Ultraviolet and Fluorescence Spectra of Proteins
AbstractA workable approach named xTB-sTDDFT was selected to investigate the excited-state spectra of oxytocin (135 atoms), GHRP-6 (120 atoms) and insulin (793 atoms). Three different Hartree –Fock components functionals (wB97XD3: 51%, LC-BLYP: 53%, wB97X: 57%) were used to calculate the excitation spectra, and the results calculated by wB97XD3 functional well agree with the experiments. It’s a deep impression that computed time cost reduced by more than 80%. For polypeptide (oxytoci n and GHRP-6), both UV and fluorescence spectra were obtained, and the errors between the calculated and experimental values approximatel...
Source: Interdisciplinary Sciences, Computational Life Sciences - November 13, 2020 Category: Bioinformatics Source Type: research

Mathematical Modeling of Calcium Oscillatory Patterns in a Neuron
AbstractCalcium oscillations are an imperative mode of signaling phenomenon. These oscillations are due to the active interactions taking place between some of the parameters like voltage gated calcium channels (VGCC), sodium calcium exchanger (NCX), calcium binding buffers, endoplasmic reticulum (ER) and mitochondria. The present paper focuses on the problem of higher level of calcium concentration in neurons which may further result into Alzheimer ’s Disease (AD). For this, a three-dimensional mathematical model having a system of differential equations depicting the changes in cytosolic calcium (in presence of buffers...
Source: Interdisciplinary Sciences, Computational Life Sciences - November 10, 2020 Category: Bioinformatics Source Type: research

Deep-Learning-Based Segmentation and Localization of White Matter Hyperintensities on Magnetic Resonance Images
In this study, we implemented four segmentation algorithms and compared the performances quantitatively and qualitatively on two open-access datasets. The location-specific analysis was conducted sequentially on 213 clinical patients with cerebral ischemia and lacune. The experimental results suggest that our deep-learning-based model has the potential to be integrated into the clinical workflow. (Source: Interdisciplinary Sciences, Computational Life Sciences)
Source: Interdisciplinary Sciences, Computational Life Sciences - November 2, 2020 Category: Bioinformatics Source Type: research

Correlations Between Phenotypes and Biological Process Ontologies in Monogenic Human Diseases
AbstractA substantial body of research is focused to improve the understanding of the relationship between genotypes and phenotypes. Genotype –phenotype studies have shown promise in improving disease diagnosis in humans and identification of specific clinical phenotypes may be helpful in developing more effective therapeutic and diagnostic strategies. To expand on the existing paradigm of evaluating genotypes and phenotypes, we present an investigation of the correlation between biological processes as represented by genomic information and phenotypes in human disease. We focus on monogenic diseases and link biological ...
Source: Interdisciplinary Sciences, Computational Life Sciences - October 28, 2020 Category: Bioinformatics Source Type: research

Predicting Hot Spot Residues at Protein –DNA Binding Interfaces Based on Sequence Information
AbstractHot spot residues at protein –DNA binding interfaces are hugely important for investigating the underlying mechanism of molecular recognition. Currently, there are a few tools available for identifying the hot spot residues in the protein–DNA complexes. In addition, the three-dimensional protein structures are needed in the se tools. However, it is well known that the three-dimensional structures are unavailable for most proteins. Considering the limitation, we proposed a method, named SPDH, for predicting hot spot residues only based on protein sequences. Firstly, we obtained 133 features from physicochemical ...
Source: Interdisciplinary Sciences, Computational Life Sciences - October 17, 2020 Category: Bioinformatics Source Type: research

Network Pharmacology Analysis to Uncover the Potential Mechanisms of Lycium barbarum on Colorectal Cancer
ConclusionOur work successfully predicted the functioning ingredients and potential targets ofL. barbarum in CRC and illustrated the potential pathways and mechanisms comprehensively. Nevertheless, these results still call for in vitro and in vivo experiments to validate. (Source: Interdisciplinary Sciences, Computational Life Sciences)
Source: Interdisciplinary Sciences, Computational Life Sciences - October 13, 2020 Category: Bioinformatics Source Type: research

PendoTMBase: A Database for Plant Endogenous Target Mimics
AbstractWith fast-evolving next-generation sequencing technology, a great amount of plant genome and transcriptome data are becoming available. Due to the availability of mature microRNA (miRNA) sequence information from the miRBase (release 21) database, it is possible to predict endogenous target mimics (eTMs) in plant by searching seed-matched target sites. We identified a total of 2669 non-redundant eTM records in 43 plant species to create a specialized web-based database platform. The platform is named PendoTMBase, which can provide details of the eTMs. Predicted pairing structure between eTMs and their target miRNA,...
Source: Interdisciplinary Sciences, Computational Life Sciences - September 29, 2020 Category: Bioinformatics Source Type: research

Theoretical Research on Excited States: Ultraviolet and Fluorescence Spectra of Aromatic Amino Acids
AbstractUsing Gaussian and Orca, UV and fluorescence spectra of three amino acids (Tyr: Tyrosine, Trp: Tryptophan, Phe: Phenylalanine) were calculated by different functionals (B3LYP, BP86, wB97X). The spectra calculated by BP86 are consistent with the experiments. UV spectra peak of Tyr is 255  nm (Exp. 275 nm, Δλ = 20 nm), Trp is 279 nm (Exp. 277 nm, Δλ = 2 nm), and Phe is 275 nm (Exp. 257 nm, Δλ = 18 nm). Fluorescence spectra peak of Trp is 341 nm (Exp. 350 nm, Δλ = 9 nm), Tyr is 295 nm (Exp. 306 nm, Δλ = 11 nm), and Phe is 285 nm (Exp. 302  nm, Δλ = 17 nm). Moreover...
Source: Interdisciplinary Sciences, Computational Life Sciences - September 25, 2020 Category: Bioinformatics Source Type: research

COVID19XrayNet: A Two-Step Transfer Learning Model for the COVID-19 Detecting Problem Based on a Limited Number of Chest X-Ray Images
This study proposed a two-step transfer learning pipeline and a deep residual network framework COVID19XrayNet for the COVID-19 detection problem based on chest X-ray images. COVID19XrayNet firstly tunes the transferred model on a large dataset of chest X-ray images, which is further tuned using a small dataset of annotated chest X-ray images. The final model achieved 0.9108 accuracy. The experimental data also suggested that the model may be improved with more training samples being released.Graphic abstractCOVID19XrayNet, a two-step transfer learning framework designed for biomedical images. (Source: Interdisciplinary Sc...
Source: Interdisciplinary Sciences, Computational Life Sciences - September 20, 2020 Category: Bioinformatics Source Type: research

Popular Computational Tools Used for miRNA Prediction and Their Future Development Prospects
AbstractMicroRNAs (miRNAs) are 19 –24 nucleotide (nt)-long noncoding, single-stranded RNA molecules that play significant roles in regulating the gene expression, growth, and development of plants and animals. From the year that miRNAs were first discovered until the beginning of the twenty-first century, researchers used experime ntal methods such as cloning and sequencing to identify new miRNAs and their roles in the posttranscriptional regulation of protein synthesis. Later, in the early 2000s, informatics approaches to the discovery of new miRNAs began to be implemented. With increasing knowledge about miRNA, more ef...
Source: Interdisciplinary Sciences, Computational Life Sciences - September 20, 2020 Category: Bioinformatics Source Type: research

The Landscape of Micro-Inversions Provide Clues for Population Genetic Analysis of Humans
ConclusionsWe propose that MIs are potential evolutionary markers for investigating population dynamics. Our results revealed the diversity of MIs in human populations and showed that they are essential to construct human population relationships and have a potential effect on human health. (Source: Interdisciplinary Sciences, Computational Life Sciences)
Source: Interdisciplinary Sciences, Computational Life Sciences - September 13, 2020 Category: Bioinformatics Source Type: research

A Novel Human Diabetes Biomarker Recognition Approach Using Fuzzy Rough Multigranulation Nearest Neighbour Classifier Model
This article proposes a novel fuzzy-rough set-based gene expression features selection using fuzzy-rough reduct under multi-granular space for human diabetes patient. Firstly, fuzzy multi-granular gain has been computed from the expression datasets via fuzzy entropy which reduces the dimension of the database. Thereafter, the features have been selected from microarray using the fuzzy rough reduct and information gain with respect to their expression patterns. To reduce the computational cost, a decision making scheme has been designed using a rough approximation of a fuzzy concept in the field of multi-granulation framewo...
Source: Interdisciplinary Sciences, Computational Life Sciences - September 11, 2020 Category: Bioinformatics Source Type: research

Impact of Gene Biomarker Discovery Tools Based on Protein –Protein Interaction and Machine Learning on Performance of Artificial Intelligence Models in Predicting Clinical Stages of Breast Cancer
In this study, three well-known biomarker identification methods (i.e., ClusterOne, MCODE, and BioDiscML) were employed in order to identify the potential biomarkers. Then, the methods were ranked and evaluated using nonlinear classification models developed based on the identified sets of biomarkers. A combined BC microarray dataset consisting of GSE124647, GSE124646, and GSE15852 was used as training set, and two test datasets, GSE15852 and GSE25066, were used for the performance measurement of the trained models. The validation of the proposed models was carried out internally (leave-one-out, fivefold and tenfold cross-...
Source: Interdisciplinary Sciences, Computational Life Sciences - September 9, 2020 Category: Bioinformatics Source Type: research