Computer-Assisted Discovery of < em > Salvia fruticosa < /em > Compounds With Schistosomicidal Activity
This study focuses on identifying potential antischistosomal compounds from the plant Salvia fruticosa. We virtually screened a library of 163 S fruticosa compounds by docking against Schistosoma mansoni sulfotransferase (SmSULT) using the PyRx software. Docking scores ranged from -4.7 to -9.3 kcal/mol. Compounds with binding affinity of -7.6 or stronger were subjected to drug-likeness assessments using the DataWarrior software. We also employed the PAINS removal tool to filter off false-positive results. Twelve compounds passed the drug-likeness screen, and these were subjected to in silico toxicity predictions to determi...
Source: Bioinformatics and Biology Insights - March 29, 2024 Category: Bioinformatics Authors: Ryman Shoko Farirai Mandivenga Source Type: research
Computer-Assisted Discovery of < em > Salvia fruticosa < /em > Compounds With Schistosomicidal Activity
This study focuses on identifying potential antischistosomal compounds from the plant Salvia fruticosa. We virtually screened a library of 163 S fruticosa compounds by docking against Schistosoma mansoni sulfotransferase (SmSULT) using the PyRx software. Docking scores ranged from -4.7 to -9.3 kcal/mol. Compounds with binding affinity of -7.6 or stronger were subjected to drug-likeness assessments using the DataWarrior software. We also employed the PAINS removal tool to filter off false-positive results. Twelve compounds passed the drug-likeness screen, and these were subjected to in silico toxicity predictions to determi...
Source: Bioinformatics and Biology Insights - March 29, 2024 Category: Bioinformatics Authors: Ryman Shoko Farirai Mandivenga Source Type: research
Computer-Assisted Discovery of < em > Salvia fruticosa < /em > Compounds With Schistosomicidal Activity
This study focuses on identifying potential antischistosomal compounds from the plant Salvia fruticosa. We virtually screened a library of 163 S fruticosa compounds by docking against Schistosoma mansoni sulfotransferase (SmSULT) using the PyRx software. Docking scores ranged from -4.7 to -9.3 kcal/mol. Compounds with binding affinity of -7.6 or stronger were subjected to drug-likeness assessments using the DataWarrior software. We also employed the PAINS removal tool to filter off false-positive results. Twelve compounds passed the drug-likeness screen, and these were subjected to in silico toxicity predictions to determi...
Source: Bioinformatics and Biology Insights - March 29, 2024 Category: Bioinformatics Authors: Ryman Shoko Farirai Mandivenga Source Type: research
Feature-specific quantile normalization and feature-specific mean –variance normalization deliver robust bi-directional classification and feature selection performance between microarray and RNAseq data
Cross-platform normalization seeks to minimize technological bias between microarray and RNAseq whole-transcriptome data. Incorporating multiple gene expression platforms permits external validation of experim... (Source: BMC Bioinformatics)
Source: BMC Bioinformatics - March 29, 2024 Category: Bioinformatics Authors: Daniel Skubleny, Sunita Ghosh, Jennifer Spratlin, Daniel E. Schiller and Gina R. Rayat Tags: Research Source Type: research
Towards a unified medical microbiome ecology of the OMU for metagenomes and the OTU for microbes
Metagenomic sequencing technologies offered unprecedented opportunities and also challenges to microbiology and microbial ecology particularly. The technology has revolutionized the studies of microbes and ena... (Source: BMC Bioinformatics)
Source: BMC Bioinformatics - March 29, 2024 Category: Bioinformatics Authors: Zhanshan (Sam) Ma Tags: Research Source Type: research
Curare and GenExVis: a versatile toolkit for analyzing and visualizing RNA-Seq data
Even though high-throughput transcriptome sequencing is routinely performed in many laboratories, computational analysis of such data remains a cumbersome process often executed manually, hence error-prone and... (Source: BMC Bioinformatics)
Source: BMC Bioinformatics - March 29, 2024 Category: Bioinformatics Authors: Patrick Blumenkamp, Max Pfister, Sonja Diedrich, Karina Brinkrolf, Sebastian Jaenicke and Alexander Goesmann Tags: Software Source Type: research
DAE-CFR: detecting microRNA-disease associations using deep autoencoder and combined feature representation
MicroRNA (miRNA) has been shown to play a key role in the occurrence and progression of diseases, making uncovering miRNA-disease associations vital for disease prevention and therapy. However, traditional lab... (Source: BMC Bioinformatics)
Source: BMC Bioinformatics - March 29, 2024 Category: Bioinformatics Authors: Yanling Liu, Ruiyan Zhang, Xiaojing Dong, Hong Yang, Jing Li, Hongyan Cao, Jing Tian and Yanbo Zhang Tags: Research Source Type: research
Identification of COVID-19 with CT scans using radiomics and DL-based features
AbstractDeep learning plays a crucial role in identifying COVID-19 patients from computed tomography (CT) scans by leveraging its ability to analyze vast amounts of image data and extract patterns indicative of the disease. While deep learning-based models have consistently achieved state-of-the-art performance, the incorporation of relevant handcrafted features alongside deep learning-based features has the potential to enhance overall performance even further. Therefore, this paper proposes a hybrid approach that combines handcrafted and deep learning features from CT scan images for accurate COVID-19 classification. Han...
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - March 29, 2024 Category: Bioinformatics Source Type: research
Meta-DHGNN: method for CRS-related cytokines analysis in CAR-T therapy based on meta-learning directed heterogeneous graph neural network
In this study, we propose Meta-DHGNN, a directed and heterogeneous graph neural network analysis method based on meta-learning. The proposed method integrates both directed and heterogeneous algorithms, while the meta-learning module effectively addresses the issue of limited data availability. This approach enables comprehensive analysis of the cytokine network and accurate prediction of CRS-related cytokines. Firstly, to tackle the challenge posed by small datasets, a pre-training phase is conducted using the meta-learning module. Consequently, the directed algorithm constructs an adjacency matrix that accurately capture...
Source: Briefings in Bioinformatics - March 28, 2024 Category: Bioinformatics Authors: Zhenyu Wei Chengkui Zhao Min Zhang Jiayu Xu Nan Xu Shiwei Wu Xiaohui Xin Lei Yu Weixing Feng Source Type: research
Epigenome-augmented eQTL-hotspots reveal genome-wide transcriptional programs in 36 human tissues
Brief Bioinform. 2024 Mar 27;25(3):bbae109. doi: 10.1093/bib/bbae109.ABSTRACTExpression quantitative trait loci (eQTLs) are used to inform the mechanisms of transcriptional regulation in eukaryotic cells. However, the specificity of genome-wide eQTL identification is limited by stringent control for false discoveries. Here, we described a method based on the non-homogeneous Poisson process to identify 125 489 regions with highly frequent, multiple eQTL associations, or 'eQTL-hotspots', from the public database of 59 human tissues or cell types. We stratified the eQTL-hotspots into two classes with their distinct sequence a...
Source: Briefings in Bioinformatics - March 28, 2024 Category: Bioinformatics Authors: Huanhuan Liu Qinwei Chen Jintao Guo Ying Zhou Zhiyu You Jun Ren Yuanyuan Zeng Jing Yang Jialiang Huang Qiyuan Li Source Type: research
Generalized reporter score-based enrichment analysis for omics data
Brief Bioinform. 2024 Mar 27;25(3):bbae116. doi: 10.1093/bib/bbae116.ABSTRACTEnrichment analysis contextualizes biological features in pathways to facilitate a systematic understanding of high-dimensional data and is widely used in biomedical research. The emerging reporter score-based analysis (RSA) method shows more promising sensitivity, as it relies on P-values instead of raw values of features. However, RSA cannot be directly applied to multi-group and longitudinal experimental designs and is often misused due to the lack of a proper tool. Here, we propose the Generalized Reporter Score-based Analysis (GRSA) method fo...
Source: Briefings in Bioinformatics - March 28, 2024 Category: Bioinformatics Authors: Chen Peng Qiong Chen Shangjin Tan Xiaotao Shen Chao Jiang Source Type: research
Review and meta-analysis of the genetic Minimal Cut Set approach for gene essentiality prediction in cancer metabolism
Brief Bioinform. 2024 Mar 27;25(3):bbae115. doi: 10.1093/bib/bbae115.ABSTRACTCancer metabolism is a marvellously complex topic, in part, due to the reprogramming of its pathways to self-sustain the malignant phenotype in the disease, to the detriment of its healthy counterpart. Understanding these adjustments can provide novel targeted therapies that could disrupt and impair proliferation of cancerous cells. For this very purpose, genome-scale metabolic models (GEMs) have been developed, with Human1 being the most recent reconstruction of the human metabolism. Based on GEMs, we introduced the genetic Minimal Cut Set (gMCS)...
Source: Briefings in Bioinformatics - March 28, 2024 Category: Bioinformatics Authors: Danel Olaverri-Mendizabal Luis V Valc árcel Naroa Barrena Carlos J Rodr íguez Francisco J Planes Source Type: research
Second-Order Effects of Chemotherapy Pharmacodynamics and Pharmacokinetics on Tumor Regression and Cachexia
Bull Math Biol. 2024 Mar 28;86(5):47. doi: 10.1007/s11538-024-01278-0.ABSTRACTDrug dose response curves are ubiquitous in cancer biology, but these curves are often used to measure differential response in first-order effects: the effectiveness of increasing the cumulative dose delivered. In contrast, second-order effects (the variance of drug dose) are often ignored. Knowledge of second-order effects may improve the design of chemotherapy scheduling protocols, leading to improvements in tumor response without changing the total dose delivered. By considering treatment schedules with identical cumulative dose delivered, we...
Source: Bulletin of Mathematical Biology - March 28, 2024 Category: Bioinformatics Authors: Luke Pierik Patricia McDonald Alexander R A Anderson Jeffrey West Source Type: research
Review and meta-analysis of the genetic Minimal Cut Set approach for gene essentiality prediction in cancer metabolism
Brief Bioinform. 2024 Mar 27;25(3):bbae115. doi: 10.1093/bib/bbae115.ABSTRACTCancer metabolism is a marvellously complex topic, in part, due to the reprogramming of its pathways to self-sustain the malignant phenotype in the disease, to the detriment of its healthy counterpart. Understanding these adjustments can provide novel targeted therapies that could disrupt and impair proliferation of cancerous cells. For this very purpose, genome-scale metabolic models (GEMs) have been developed, with Human1 being the most recent reconstruction of the human metabolism. Based on GEMs, we introduced the genetic Minimal Cut Set (gMCS)...
Source: Briefings in Bioinformatics - March 28, 2024 Category: Bioinformatics Authors: Danel Olaverri-Mendizabal Luis V Valc árcel Naroa Barrena Carlos J Rodr íguez Francisco J Planes Source Type: research
Generalized reporter score-based enrichment analysis for omics data
Brief Bioinform. 2024 Mar 27;25(3):bbae116. doi: 10.1093/bib/bbae116.ABSTRACTEnrichment analysis contextualizes biological features in pathways to facilitate a systematic understanding of high-dimensional data and is widely used in biomedical research. The emerging reporter score-based analysis (RSA) method shows more promising sensitivity, as it relies on P-values instead of raw values of features. However, RSA cannot be directly applied to multi-group and longitudinal experimental designs and is often misused due to the lack of a proper tool. Here, we propose the Generalized Reporter Score-based Analysis (GRSA) method fo...
Source: Briefings in Bioinformatics - March 28, 2024 Category: Bioinformatics Authors: Chen Peng Qiong Chen Shangjin Tan Xiaotao Shen Chao Jiang Source Type: research
