Top Research Papers on Bioinformatics

A comprehensive review comparing Venn diagram generators and application tools to assist users in selecting suitable tools for analyzing and visualizing user-defined datasets is performed.

Recent key developments in ensemble deep learning are shared and a look is looked at at how their contribution has benefited a wide range of bioinformatics research from basic sequence analysis to systems biology.

The Bio3D‐eddm package supports both experimental and theoretical simulation‐generated structures, is integrated with other methods for dissecting sequence‐structure–function relationships, and can be used in a highly automated and reproducible manner.

This review collected about 100 circRNA-associated bioinformatics tools and summarized their current attributes and capabilities and performed network analysis and text mining on circRNA tool publications in order to reveal trends in their ongoing development.

Nanopore sequencing is being applied in genome assembly, full-length transcript detection and base modification detection and in more specialized areas, such as rapid clinical diagnoses and outbreak surveillance.

The state of fully homomorphic encryption for privacy-preserving techniques in machine learning and bioinformatics is reviewed, along with descriptions of how these methods can be implemented in the encrypted domain.

Artificial intelligence (AI) systems utilizing deep neural networks and machine learning (ML) algorithms are widely used for solving critical problems in bioinformatics, biomedical informatics and precision medicine. However, complex ML models that are often perceived as opaque and black-box methods make it difficult to understand the reasoning behind their decisions. This lack of transparency can be a challenge for both end-users and decision-makers, as well as AI developers. In sensitive areas such as healthcare, explainability and accountability are not only desirable properties but also le...

The challenges posed for machine learning, and, in particular, deep learning in biomedicine, are outlined, and unique opportunities for machinelearning techniques integrated with established bioinformatics approaches are suggested to overcome some of these challenges.

An historical chronicle of how R became what it is today is provided, describing all its current features and capabilities, and the role of R in science in general as a driver for reproducibility is discussed.

Detailed information is provided on utilizing the three most widely accessed tools within the MPI Bioinformatics Toolkit: HHpred for the detection of homologs, HHpred in conjunction with MODELLER for structure prediction and homology modeling, and CLANS for the visualization of relationships in large sequence datasets.

The CK/PCr system acts as a dynamic biosensor based on chemo-mechanical energy transduction, which might explain why dysregulation in Cr metabolism contributes to a wide range of diseases besides the mitigating effect that Cr supplementation may have in some of these disease states.

This study aimed to use bioinformatic methods to identify the key biomarkers and immune infiltration in osteoarthritis using the ConsensusClusterPlus package in R software using a consistent clustering approach.

This work provides a comprehensive survey of emerging graph representation learning algorithms and their applications in bioinformatics from molecular level to genomics, pharmaceutical and healthcare systems level and categorize and analyze both graph embedding methods and graph neural networks.

Key developments of transformer-based language models are introduced by describing the detailed structure of transformers and the common challenges, including heterogeneity of training data, computational expense and model interpretability, and opportunities in the context of bioinformatics research are identified.

The PyMod project is designed to act as a fully integrated interface between the popular molecular graphics viewer PyMOL, and some of the most frequently used tools for structural bioinformatics, e.g. BLAST, HMMER, Clustal, MUSCLE, PSIPRED, DOPE and MODELLER.

Augur is a bioinformatics toolkit designed for phylogenetic analyses of human pathogens that must scale rapidly with the number of samples and be flexible enough to adapt to a variety of questions and organisms.

Tools, rules and incentives are buckling under the flood of coronavirus genome sequences — to help control the pandemic, researchers need new approaches. Tools, rules and incentives are buckling under the flood of coronavirus genome sequences — to help control the pandemic, researchers need new approaches.

This review introduces bioinformatics software and tools designed for mass spectrometry-based protein identification and quantification, and then reviews the different statistical and machine learning methods that have been developed to perform comprehensive analysis in proteomics studies.

In this review, insights are provided into in silico epitope-based vaccine design and vaccinology procedures used for the development of the next-generation vaccines with high effectiveness.

This Perspective highlights workflow managers, which are useful for developing and managing complex bioinformatics pipelines, and outlines community-curated pipeline initiatives that enable novice and experienced users to perform complex, best-practice analyses without having to manually assemble workflows.