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.

EPI-Mind: Identifying Enhancer –Promoter Interactions Based on Transformer Mechanism
ConclusionThis research proposed a method, which was called EPI-Mind, to predict EPIs only with enhancer and promoters sequences, the framework of which was based on deep learning. This manuscript may provide a new route to solve the problem.Graphical abstract (Source: Interdisciplinary Sciences, Computational Life Sciences)
Source: Interdisciplinary Sciences, Computational Life Sciences - July 30, 2022 Category: Bioinformatics Source Type: research

Correction to: Gene Selection in a Single Cell Gene Space Based on D –S Evidence Theory
The original article has been corrected. (Source: Interdisciplinary Sciences, Computational Life Sciences)
Source: Interdisciplinary Sciences, Computational Life Sciences - July 30, 2022 Category: Bioinformatics Source Type: research

FEAMR: A Database for Surveillance of Food and Environment-Associated Antimicrobial Resistance
AbstractThe rapid dissemination of antimicrobial resistance (AMR) has emerged as a serious health problem on an unprecedented global scale. AMR is predicted to kill more than 10 million people annually by 2050 leading to huge economic losses worldwide. Therefore, urgent action is required at the national as well as international levels to avert this looming crisis. Effective surveillance can play an important role in the containment of AMR spread by providing data to help determine AMR hotspots, predict an outbreak, maintain proper stewardship and propose immediate and future plans of action in this respect. Although many ...
Source: Interdisciplinary Sciences, Computational Life Sciences - July 25, 2022 Category: Bioinformatics Source Type: research

ASI-DBNet: An Adaptive Sparse Interactive ResNet-Vision Transformer Dual-Branch Network for the Grading of Brain Cancer Histopathological Images
AbstractBrain cancer is the deadliest cancer that occurs in the brain and central nervous system, and rapid and precise grading is essential to reduce patient suffering and improve survival. Traditional convolutional neural network (CNN)-based computer-aided diagnosis algorithms cannot fully utilize the global information of pathology images, and the recently popular vision transformer (ViT) model does not focus enough on the local details of pathology images, both of which lead to a lack of precision in the focus of the model and a lack of accuracy in the grading of brain cancer. To solve this problem, we propose an adapt...
Source: Interdisciplinary Sciences, Computational Life Sciences - July 9, 2022 Category: Bioinformatics Source Type: research

A Novel Multitasking Ant Colony Optimization Method for Detecting Multiorder SNP Interactions
AbstractMotivationLinear or nonlinear interactions of multiple single-nucleotide polymorphisms (SNPs) play an important role in understanding the genetic basis of complex human diseases. However, combinatorial analytics in high-dimensional space makes it extremely challenging to detect multiorder SNP interactions. Most classic approaches can only perform one task (for detectingk-order SNP interactions) in each run. Since prior knowledge of a complex disease is usually not available, it is difficult to determine the value ofk for detectingk-order SNP interactions.MethodsA novel multitasking ant colony optimization algorithm...
Source: Interdisciplinary Sciences, Computational Life Sciences - July 5, 2022 Category: Bioinformatics Source Type: research

Diagnosis of Pancreatic Cancer Using miRNA30e Biosensor
AbstractThis work describes miRNA-based electrochemical biosensor for detection of miRNA30e, a pancreatic cancer biomarker. The screen-printed gold electrode was functionalized using cysteine hydrochloride followed by immobilization of synthesized colloidal gold nanorods (10 –12 nm diameter and 25–65 nm length). The gold nanorods modified electrode surface was amino functionalized for covalent attachment of single-stranded DNA probe against miRNA30e (miR30e). This platform was utilized for electrochemical measurements and response analysis of target miRNA30e. Elec trochemical impedance spectroscopic measurements show...
Source: Interdisciplinary Sciences, Computational Life Sciences - July 3, 2022 Category: Bioinformatics Source Type: research

Deep Residual Network for Diagnosis of Retinal Diseases Using Optical Coherence Tomography Images
In this study, we propose a deep residual network for the classification of four classes of retinal diseases, namely diabetic macular edema (DME), choroidal neovascularization (CNV), DRUSEN and NORMAL in OCT images. The proposed model is based on the popular architecture called ResNet50, which eliminates the vanishing gradient problem and is pre-trained on large dataset such as ImageNet and trained end-to-end on the publicly available OCT image dataset. We removed the fully connected layer of ResNet50 and placed our new fully connected block on top to improve the classification accuracy and avoid overfitting in the propose...
Source: Interdisciplinary Sciences, Computational Life Sciences - June 29, 2022 Category: Bioinformatics Source Type: research

Protein Subcellular Localization Prediction Model Based on Graph Convolutional Network
AbstractProtein subcellular localization prediction is an important research area in bioinformatics, which plays an essential role in understanding protein function and mechanism. Many machine learning and deep learning algorithms have been employed for this task, but most of them do not use structural information of proteins. With the advances in protein structure research in recent years, protein contact map prediction has been dramatically enhanced. In this paper, we present GraphLoc, a deep learning model that predicts the localization of proteins at the subcellular level. The cores of the model are a graph convolution...
Source: Interdisciplinary Sciences, Computational Life Sciences - June 17, 2022 Category: Bioinformatics Source Type: research

RNABPDB: Molecular Modeling of RNA Structure —From Base Pair Analysis in Crystals to Structure Prediction
AbstractThe stable three-dimensional structure of RNA is known to play several important biochemical roles, from post-transcriptional gene regulation to enzymatic action. These structures contain double-helical regions, which often have different types of non-canonical base pairs in addition to Watson –Crick base pairs. Hence, it is important to study their structures from experimentally obtained or even predicted ones, to understand their role, or to develop a drug against the potential targets. Molecular Modeling of RNA double helices containing non-canonical base pairs is a difficult process , particularly due to the ...
Source: Interdisciplinary Sciences, Computational Life Sciences - June 15, 2022 Category: Bioinformatics Source Type: research

HODD: A Manually Curated Database of Human Ophthalmic Diseases with Symptom Characteristics and Genetic Variants Towards Facilitating Quick and Definite Diagnosis
AbstractOphthalmic diseases are disorders that affect the eyes. Hundreds of causal genes and biological pathways have been reported to be closely correlated with ophthalmic diseases. However, these information are scattered across various resources, which has hindered a thorough and deep understanding of ophthalmic diseases. In the present work, we proposed the Human Ophthalmic Diseases Database (HODD), which currently deposits 730 ophthalmic diseases and 653 related genes and is available athttp://bio-bigdata.cn/HODD/. The disease-related information and genes related to ophthalmic diseases were collected from the several...
Source: Interdisciplinary Sciences, Computational Life Sciences - May 21, 2022 Category: Bioinformatics Source Type: research

In silico Methods for Identification of Potential Therapeutic Targets
AbstractAt the initial stage of drug discovery, identifying novel targets with maximal efficacy and minimal side effects can improve the success rate and portfolio value of drug discovery projects while simultaneously reducing cycle time and cost. However, harnessing the full potential of big data to narrow the range of plausible targets through existing computational methods remains a key issue in this field. This paper reviews two categories of in silico methods —comparative genomics and network-based methods—for finding potential therapeutic targets among cellular functions based on understanding their related biolo...
Source: Interdisciplinary Sciences, Computational Life Sciences - May 21, 2022 Category: Bioinformatics Source Type: research

FTWSVM-SR: DNA-Binding Proteins Identification via Fuzzy Twin Support Vector Machines on Self-Representation
In this study, a fuzzy twin support vector machine (FTWSVM) is employed to detect DBPs. First, multiple types of protein sequence features are formed into kernel matrices; Then, multiple kernel learning (MKL) algorithm is utilized to linear combine multiple kernels; next, self-representation-based membership function is utilized to estimate membership value (weight) of each training sample; finally, we feed the integrated kernel matrix and membership values into the FTWSVM-SR model for training and testing. On comparison with other predictive models, FTWSVM based on SR (FTWSVM-SR) obtains the best performance of Matthew �...
Source: Interdisciplinary Sciences, Computational Life Sciences - May 21, 2022 Category: Bioinformatics Source Type: research

Consistent Clustering Pattern of Prokaryotic Genes Based on Base Frequency at the Second Codon Position and its Association with Functional Category Preference
AbstractIn 2002, our research group observed a gene clustering pattern based on the base frequency of A versus T at the second codon position in the genome ofVibrio cholera and found that the functional category distribution of genes in the two clusters was different. With the availability of a large number of sequenced genomes, we performed a systematic investigation of A2–T2 distribution and found that 2694 out of 2764 prokaryotic genomes have an optimal clustering number of two, indicating a consistent pattern. Analysis of the functional categories of the coding genes in each cluster in 1483 prokaryotic genomes indica...
Source: Interdisciplinary Sciences, Computational Life Sciences - May 21, 2022 Category: Bioinformatics Source Type: research

A Visual Phenotype-Based Differential Diagnosis Process for Rare Diseases
ConclusionCompared to genetic and molecular analysis, phenotype-based diagnosis is faster, cheaper, and easier. The differential diagnosis process we designed can optimize the phenotype information of patients and better locate the target disease. It can also help to make screening decisions before genetic testing.Graphical Abstract (Source: Interdisciplinary Sciences, Computational Life Sciences)
Source: Interdisciplinary Sciences, Computational Life Sciences - May 21, 2022 Category: Bioinformatics Source Type: research

easyMF: A Web Platform for Matrix Factorization-Based Gene Discovery from Large-scale Transcriptome Data
AbstractWith the development of high-throughput experimental technologies, large-scale RNA sequencing (RNA-Seq) data have been and continue to be produced, but have led to challenges in extracting relevant biological knowledge hidden in the produced high-dimensional gene expression matrices. Here, we develop easyMF (https://github.com/cma2015/easyMF), a web platform that can facilitate functional gene discovery from large-scale transcriptome data using matrix factorization (MF) algorithms. Compared with existing MF-based software packages, easyMF exhibits several promising features, such as greater functionality, flexibili...
Source: Interdisciplinary Sciences, Computational Life Sciences - May 18, 2022 Category: Bioinformatics Source Type: research