Correction to: Inflated false discovery rate due to volcano plots: problem and solutions
Brief Bioinform. 2024 Mar 27;25(3):bbae149. doi: 10.1093/bib/bbae149.NO ABSTRACTPMID:38619418 | DOI:10.1093/bib/bbae149 (Source: Briefings in Bioinformatics)
Source: Briefings in Bioinformatics - April 15, 2024 Category: Bioinformatics Source Type: research
Correction to: DeepFormer: a hybrid network based on convolutional neural network and flow-attention mechanism for identifying the function of DNA sequences
Brief Bioinform. 2024 Mar 27;25(3):bbae181. doi: 10.1093/bib/bbae181.NO ABSTRACTPMID:38619419 | DOI:10.1093/bib/bbae181 (Source: Briefings in Bioinformatics)
Source: Briefings in Bioinformatics - April 15, 2024 Category: Bioinformatics Source Type: research
MGCNSS: miRNA-disease association prediction with multi-layer graph convolution and distance-based negative sample selection strategy
In this study, we propose a novel approach named MGCNSS with the multi-layer graph convolution and high-quality negative sample selection strategy. Specifically, MGCNSS first constructs a comprehensive heterogeneous network by integrating miRNA and disease similarity networks coupled with their known association relationships. Then, we employ the multi-layer graph convolution to automatically capture the meta-path relations with different lengths in the heterogeneous network and learn the discriminative representations of miRNAs and diseases. After that, MGCNSS establishes a highly reliable negative sample set from the unl...
Source: Briefings in Bioinformatics - April 15, 2024 Category: Bioinformatics Authors: Zhen Tian Chenguang Han Lewen Xu Zhixia Teng Wei Song Source Type: research
Fuzzy kernel evidence Random Forest for identifying pseudouridine sites
In this study, we propose fuzzy kernel evidence Random Forest (FKeERF) to identify pseudouridine sites. This method is called PseU-FKeERF, which demonstrates high accuracy in identifying pseudouridine sites from RNA sequencing data. The PseU-FKeERF model selected four RNA feature coding schemes with relatively good performance for feature combination, and then input them into the newly proposed FKeERF method for category prediction. FKeERF not only uses fuzzy logic to expand the original feature space, but also combines kernel methods that are easy to interpret in general for category prediction. Both cross-validation test...
Source: Briefings in Bioinformatics - April 15, 2024 Category: Bioinformatics Authors: Mingshuai Chen Mingai Sun Xi Su Prayag Tiwari Yijie Ding Source Type: research
TLOD: Innovative ovarian tumor detection for accurate multiclass classification and clinical application
AbstractOvarian tumors pose a major threat to women's health, mostly remaining undetected until they reach advanced stages, resulting in complex treatment and decreased survival rates. Besides, tumor heterogeneity is more responsible for poor treatment response and adverse prognosis. The purpose of this research is to identify ovarian epithelial tumors in premature stage using histopathological images. In this research, we address the need for an improved ovarian tumor detection method through the development of an innovative simple intelligent approach ‘Transfer Learning with ResNet-based Deep Learning for Ovarian Tumor...
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - April 15, 2024 Category: Bioinformatics Source Type: research
Mechanistic insights into the conformational changes and alterations in residual communications due to the mutations in the pncA Gene of Mycobacterium tuberculosis: A computational perspective for effective therapeutic solutions
This study advances our knowledge of the primary cause of the mechanism of PZA resistance and the structural dynamics of pncA mutants, which will help us to design new and potent chemical scaffolds to treat drug-resistant TB (DR-TB).PMID:38615420 | DOI:10.1016/j.compbiolchem.2024.108065 (Source: Computational Biology and Chemistry)
Source: Computational Biology and Chemistry - April 14, 2024 Category: Bioinformatics Authors: Manikandan Jayaraman Rajalakshmi Kumar Santhiya Panchalingam Jeyakanthan Jeyaraman Source Type: research
Mechanistic insights into the conformational changes and alterations in residual communications due to the mutations in the pncA Gene of Mycobacterium tuberculosis: A computational perspective for effective therapeutic solutions
This study advances our knowledge of the primary cause of the mechanism of PZA resistance and the structural dynamics of pncA mutants, which will help us to design new and potent chemical scaffolds to treat drug-resistant TB (DR-TB).PMID:38615420 | DOI:10.1016/j.compbiolchem.2024.108065 (Source: Computational Biology and Chemistry)
Source: Computational Biology and Chemistry - April 14, 2024 Category: Bioinformatics Authors: Manikandan Jayaraman Rajalakshmi Kumar Santhiya Panchalingam Jeyakanthan Jeyaraman Source Type: research
Designing and delivering bioinformatics project-based learning in East Africa
The Eastern Africa Network for Bioinformatics Training (EANBiT) has matured through continuous evaluation, feedback, and codesign. We highlight how the program has evolved to meet challenges and achieve its go... (Source: BMC Bioinformatics)
Source: BMC Bioinformatics - April 14, 2024 Category: Bioinformatics Authors: Caleb K. Kibet, Jean-Baka Domelevo Entfellner, Daudi Jjingo, Etienne Pierre de Villiers, Santie de Villiers, Karen Wambui, Sam Kinyanjui and Daniel Masiga Tags: Research Source Type: research
The simulation experiment description markup language (SED-ML): language specification for level 1 version 5
J Integr Bioinform. 2024 Apr 15. doi: 10.1515/jib-2024-0008. Online ahead of print.ABSTRACTModern biological research is increasingly informed by computational simulation experiments, which necessitate the development of methods for annotating, archiving, sharing, and reproducing the conducted experiments. These simulations increasingly require extensive collaboration among modelers, experimentalists, and engineers. The Minimum Information About a Simulation Experiment (MIASE) guidelines outline the information needed to share simulation experiments. SED-ML is a computer-readable format for the information outlined by MIAS...
Source: Journal of integrative bioinformatics - April 13, 2024 Category: Bioinformatics Authors: Lucian P Smith Frank T Bergmann Alan Garny Tom áš Helikar Jonathan Karr David Nickerson Herbert Sauro Dagmar Waltemath Matthias K önig Source Type: research
MMR: A Multi-view Merge Representation model for Chemical-Disease relation extraction
Comput Biol Chem. 2024 Apr 3;110:108063. doi: 10.1016/j.compbiolchem.2024.108063. Online ahead of print.ABSTRACTChemical-Disease relation (CDR) extraction aims to identify the semantic relations between chemical and disease entities in the unstructured biomedical document, which provides a basis for downstream tasks such as clinical medical diagnosis and drug discovery. Compared with general domain relation extraction, it needs a more effective representation of the whole document due to the specialized nature of texts in the biomedical domain, including the biomedical entity and entity-pair representation. In this paper, ...
Source: Computational Biology and Chemistry - April 13, 2024 Category: Bioinformatics Authors: Yi Zhang Jing Peng Baitai Cheng Yang Liu Chi Jiang Source Type: research
The simulation experiment description markup language (SED-ML): language specification for level 1 version 5
J Integr Bioinform. 2024 Apr 15. doi: 10.1515/jib-2024-0008. Online ahead of print.ABSTRACTModern biological research is increasingly informed by computational simulation experiments, which necessitate the development of methods for annotating, archiving, sharing, and reproducing the conducted experiments. These simulations increasingly require extensive collaboration among modelers, experimentalists, and engineers. The Minimum Information About a Simulation Experiment (MIASE) guidelines outline the information needed to share simulation experiments. SED-ML is a computer-readable format for the information outlined by MIAS...
Source: Journal of integrative bioinformatics - April 13, 2024 Category: Bioinformatics Authors: Lucian P Smith Frank T Bergmann Alan Garny Tom áš Helikar Jonathan Karr David Nickerson Herbert Sauro Dagmar Waltemath Matthias K önig Source Type: research
Understanding and Quantifying Network Robustness to Stochastic Inputs
Bull Math Biol. 2024 Apr 12;86(5):55. doi: 10.1007/s11538-024-01283-3.ABSTRACTA variety of biomedical systems are modeled by networks of deterministic differential equations with stochastic inputs. In some cases, the network output is remarkably constant despite a randomly fluctuating input. In the context of biochemistry and cell biology, chemical reaction networks and multistage processes with this property are called robust. Similarly, the notion of a forgiving drug in pharmacology is a medication that maintains therapeutic effect despite lapses in patient adherence to the prescribed regimen. What makes a network robust...
Source: Bulletin of Mathematical Biology - April 12, 2024 Category: Bioinformatics Authors: Hwai-Ray Tung Sean D Lawley Source Type: research
