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.

Application of Immune Checkpoint Inhibitors in Solid Organ Transplantation Recipients: A Systematic Review
ConclusionsOur systematic review summarizes the use of ICIs in SOTRs and evaluates the efficacy of ICIs and the risk factors that induce HVGR. Through risk factor analysis, we found that mTOR inhibitors and calcineurin inhibitors may help to reduce the occurrence of HVGR;  hormones and anti-metabolic drugs may have adverse effects on the efficacy of ICIs. In addition, there is a contradictory relationship between the occurrence of HVGR and the efficacy of ICIs. (Source: Interdisciplinary Sciences, Computational Life Sciences)
Source: Interdisciplinary Sciences, Computational Life Sciences - June 21, 2021 Category: Bioinformatics Source Type: research

Sequence-Based Prediction of Transmembrane Protein Crystallization Propensity
AbstractTransmembrane proteins play a vital role in cell life activities. There are several techniques to determine transmembrane protein structures and X-ray crystallography is the primary methodology. However, due to the special properties of transmembrane proteins, it is still hard to determine their structures by X-ray crystallography technique. To reduce experimental consumption and improve experimental efficiency, it is of great significance to develop computational methods for predicting the crystallization propensity of transmembrane proteins. In this work, we proposed a sequence-based machine learning method, name...
Source: Interdisciplinary Sciences, Computational Life Sciences - June 18, 2021 Category: Bioinformatics Source Type: research

LPCANet: Classification of Laryngeal Cancer Histopathological Images Using a CNN with Position Attention and Channel Attention Mechanisms
AbstractLaryngeal cancer is one of the most common malignant tumors in otolaryngology, and histopathological image analysis is the gold standard for the diagnosis of laryngeal cancer. However, pathologists have high subjectivity in their diagnoses, which makes it easy to miss diagnoses and misdiagnose. In addition, according to a literature search, there is currently no computer-aided diagnosis (CAD) algorithm that has been applied to the classification of histopathological images of laryngeal cancer. Convolutional neural networks (CNNs) are widely used in various other cancer classification tasks. However, the potential g...
Source: Interdisciplinary Sciences, Computational Life Sciences - June 17, 2021 Category: Bioinformatics Source Type: research

Molecular Dynamics Simulations Reveal the Modulated Mechanism of STING Conformation
AbstractStimulator of interferon genes (STING), which is an integral ER-membrane protein, could induce an antiviral state and boost antitumor immunity. Recent experiments reported that different small molecules could modulate the conformation of the STING. However, the mechanism of small molecules modulating the conformation of STING is still unknown. To illustrate the conformational modulated mechanism of STING by small molecules at atomic level, we investigated the interactions between STING and the small molecules: cGAMP and diABZI with molecular dynamics (MD) simulations method. Interestingly, we found that the residue...
Source: Interdisciplinary Sciences, Computational Life Sciences - June 17, 2021 Category: Bioinformatics Source Type: research

HTRPCA: Hypergraph Regularized Tensor Robust Principal Component Analysis for Sample Clustering in Tumor Omics Data
AbstractIn recent years, clustering analysis of cancer genomics data has gained widespread attention. However, limited by the dimensions of the matrix, the traditional methods cannot fully mine the underlying geometric structure information in the data. Besides, noise and outliers inevitably exist in the data. To solve the above two problems, we come up with a new method which uses tensor to represent cancer omics data and applies hypergraph to save the geometric structure information in original data. This model is called hypergraph regularized tensor robust principal component analysis (HTRPCA). The data processed by HTR...
Source: Interdisciplinary Sciences, Computational Life Sciences - June 11, 2021 Category: Bioinformatics Source Type: research

TIPD: A Probability Distribution-Based Method for Trajectory Inference from Single-Cell RNA-Seq Data
AbstractSingle-cell RNA-seq technology provides an unprecedented opportunity to allow researchers to study the biological heterogeneity during cell differentiation and development with higher resolution. Although many computational methods have been proposed to infer cell lineages from single-cell RNA-seq data, constructing accurate cell trajectories remains a challenge. We develop a novel trajectory inference method-based probability distribution (TIPD) to describe the heterogeneity of cell population. TIPD combines signalling entropy and clustering results of the gene expression profile to describe the probability distri...
Source: Interdisciplinary Sciences, Computational Life Sciences - June 9, 2021 Category: Bioinformatics Source Type: research

Pathogenic Factors Identification of Brain Imaging and Gene in Late Mild Cognitive Impairment
In this study, we mapped them to LMCI with higher accuracies, so as to provide a more robust understanding of the physiological mechanism of MCI. (Source: Interdisciplinary Sciences, Computational Life Sciences)
Source: Interdisciplinary Sciences, Computational Life Sciences - June 9, 2021 Category: Bioinformatics Source Type: research

Preclinical Western Blot in the Era of Digital Transformation and Reproducible Research, an Eastern Perspective
AbstractThe current research is an interdisciplinary endeavor to develop a necessary tool in preclinical protein studies of diseases or disorders through western blotting. In the era of digital transformation and open access principles, an interactive cloud-based database called East –West Blot (https://rancs-lab.shinyapps.io/WesternBlots) is designed and developed. The online interactive subject-specific database built on the R shiny platform facilitates a systematic literature search on the specific subject matter, here set to western blot studies of protein regulation in the preclinical model of TBI. The tool summariz...
Source: Interdisciplinary Sciences, Computational Life Sciences - June 2, 2021 Category: Bioinformatics Source Type: research

Adaptive Total-Variation Regularized Low-Rank Representation for Analyzing Single-Cell RNA-seq Data
AbstractHigh-throughput sequencing of single-cell gene expression reveals a complex mechanism of individual cell ’s heterogeneity in a population. An important purpose for analyzing single-cell RNA sequencing (scRNA-seq) data is to identify cell subtypes and functions by cell clustering. To deal with high levels of noise and cellular heterogeneity, we introduced a new single cell data analysis model called A daptive Total-Variation Regularized Low-Rank Representation (ATV-LRR). In scRNA-seq data, ATV-LRR can reconstruct the low-rank subspace structure to learn the similarity of cells. The low-rank representation can not ...
Source: Interdisciplinary Sciences, Computational Life Sciences - June 2, 2021 Category: Bioinformatics Source Type: research

Application of Supervised Machine Learning to Extract Brain Connectivity Information from Neuroscience Research Articles
AbstractUnderstanding the complex connectivity structure of the brain is a major challenge in neuroscience. Vast and ever-expanding literature about neuronal connectivity between brain regions already exists in published research articles and databases. However, with the ever-expanding increase in published articles and repositories, it becomes difficult for a neuroscientist to engage with the breadth and depth of any given field within neuroscience. Natural Language Processing (NLP) techniques can be used to mine‘Brain Region Connectivity’ information from published articles to build a centralized connectivity resourc...
Source: Interdisciplinary Sciences, Computational Life Sciences - June 2, 2021 Category: Bioinformatics Source Type: research

Are the Allergic Reactions of COVID-19 Vaccines Caused by mRNA Constructs or Nanocarriers? Immunological Insights
AbstractThe Food and Drug Administration (FDA) has recently authorized the two messenger RNA (mRNA) vaccines BNT162b2 and mRNA-1273 for emergency use against the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causing the COVID-19 coronavirus disease. BNT162b2 and mRNA-1273 vaccines were developed by Pfizer-BioNTech and Moderna, respectively, in 2020. The United Kingdom, Bahrain, Canada, Mexico, United States, Singapore, Oman, Saudi Arabia, Kuwait, and European Union began their vaccination programs with the BNT162b2 vaccine, while the United States and Canada also started the mRNA-1273 vaccination program in ...
Source: Interdisciplinary Sciences, Computational Life Sciences - May 22, 2021 Category: Bioinformatics Source Type: research

On the Identification of Clinically Relevant Bacterial Amino Acid Changes at the Whole Genome Level Using Auto-PSS-Genome
AbstractThe identification of clinically relevant bacterial amino acid changes can be performed using different methods aimed at the identification of genes showing positively selected amino acid sites (PSS). Nevertheless, such analyses are time consuming, and the frequency of genes showing evidence for PSS can be low. Therefore, the development of a pipeline that allows the quick and efficient identification of the set of genes that show PSS is of interest. Here, we present Auto-PSS-Genome, a Compi-based pipeline distributed as a Docker image, that automates the process of identifying genes that show PSS using three diffe...
Source: Interdisciplinary Sciences, Computational Life Sciences - May 19, 2021 Category: Bioinformatics Source Type: research

The Performance Comparison of Gene Co-expression Networks of Breast and Prostate Cancer using Different Selection Criteria
This study applies three GNI algorithms on mRNA gene expression, RNA-Seq, and miRNA–target genes datasets to infer GCNs of breast and prostate cancers. To evaluate the performance of the GCNs, we utilize overlap analysis via literature data, topological assessment, an d Gene Ontology-based biological assessment. The results emphasize how the selection of biological datasets and GNI algorithms affect the performance results on different evaluation criteria. GCNs on microarray gene expression data slightly outperform in overlap analysis. Also, GCNs on RNA-Seq and g ene expression datasets follow scale-free topology. The bi...
Source: Interdisciplinary Sciences, Computational Life Sciences - May 18, 2021 Category: Bioinformatics Source Type: research

TUPDB: Target-Unrelated Peptide Data Bank
AbstractThe isolation of target-unrelated peptides (TUPs) through biopanning remains as a major problem of phage display selection experiments. These TUPs do not have any actual affinity toward targets of interest, which tend to be mistakenly identified as target-binding peptides. Therefore, an information portal for storing TUP data is urgently needed. Here, we present a TUP data bank (TUPDB), which is a comprehensive, manually curated database of approximately 73 experimentally verified TUPs and 1963 potential TUPs collected from TUPScan, the BDB database, and public research articles. The TUPScan tool has been integrate...
Source: Interdisciplinary Sciences, Computational Life Sciences - May 16, 2021 Category: Bioinformatics Source Type: research

Enhanced Evolutionary Feature Selection and Ensemble Method for Cardiovascular Disease Prediction
AbstractCardiovascular Disease (CVD) is one among the main factors for the increase in mortality rate worldwide. The analysis and prediction of this disease is yet a highly formidable task in medical data analysis. Recent advancements in technology such as Big Data, Artificial Intelligence and the need for automated models have paved the way for developing a more reliable and efficient model for predicting heart disease. Several researches have been carried out in predicting heart diseases but the focus on choosing the important attributes that play a significant role in predicting CVD is inadequate. Hence the choice of ri...
Source: Interdisciplinary Sciences, Computational Life Sciences - May 14, 2021 Category: Bioinformatics Source Type: research