Top Research Papers on Bioinformatics

This review provides an overview of the concepts of quantum biology and quantum mechanics and their intersection in quantum bioinformatics and proposes a classification of quantum bioinformatics to promote interdisciplinary collaboration and accelerate progress.

This work presents a novel method for including interface information into protein docking simulations within the LightDock framework, and demonstrates the applicability of this approach on the new 55 cases of the Protein–Protein Docking Benchmark 5.

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.

In being the Founding Dean of a new School of Data Science, what the authors do suddenly looks different, and a computational biologist with 40 years of research experience says bioinformatics is dead.

This research presents the method for identifying gateway nodes in three datasets using a high performance computing environment: quiescence in Saccharomyces cerevisiae, brain aging in Mus Musculus, and the effects of creatine on Aging in Mus musculus and finds that the parallel method improves runtime and performs equally as well as sequential approach.

This study proposed an iterative model to fine-tune instructions for guiding a ChatGPT in generating code for bioinformatics data analysis tasks and demonstrated the feasibility of the model by applying it to various bioinformics topics.

It is found that biobank-scale analyses emitted substantial kgCO2e and simple software upgrades could make GWAS greener, e.g. upgrading from BOLT-LMM v1 to v2.3 reduced carbon footprint by 73% and switching from the average data centre to a more efficient data centres can reduce carbon footprint.

This chapter presents a thorough background and deep literature review of the current topic of study, and defines the key concepts utilised throughout this investigation.

The direct application of textual foundation models on bioinformatics tasks is discussed, focusing on how to make the most out of canonical large language models and mitigate their inherent flaws.

An exploration covering, methods development, putting the "bio" back in bioinformatics, quality control, and making the leap to systems biology.

First, I apologize for the delayed publication of this Special Issue in the form of a book title, and I apologise for the delay in the publication of the book title.

The present review discusses the field of cheminformatics and proposes the use of virtual chemical libraries in virtual screening methods to increase the probability of discovering novel hit chemicals and increase the quality of the compounds as well as discover promising ones.

Statistical Rethinking frames usual methods and tools taught in graduate statistical courses into a different way to encourage the reader to understand the details and appreciate the underlying assumptions.

The goal of this review is to summarize the current metabolomics analysis workflow and its main analysis software to provide useful insights for researchers to establish a preferable pipeline of metabolomics or multi-omics analysis.

A thorough review of BioLMs is provided, focusing on their evolution, classification, and distinguishing features, alongside a detailed examination of training methodologies, datasets, and evaluation frameworks, to highlight emerging trends and future directions.

This article will look at how visualization can leverage the Metaverse in bioinformatics research, the pros and cons of this technology, and what the future may hold.

The basic concepts of deep learning are introduced and the recent advances and challenges of applying deep learning to various bioinformatics problems, such as genome sequencing, gene expression analysis, protein structure prediction, drug discovery, and disease diagnosis are surveyed.

There is a mounting need for exosome lipidomic studies to build the foundation for novel therapeutic studies that use exosomal components, and bioinformatic platforms such as “Lipidomics Informatics for Life-Science” enable fast and integrated access to these pipelines in a user-friendly manner.

: Background: The Mycobacterium tuberculosis complex (MTBC) bacteria include the slowly growing, host-associated bacteria Mycobacterium tuberculosis, Mycobacterium Bovis, Mycobacterium microti, Mycobacterium africanum, Mycobacterium pinnipedii. Aim

This special issue aims to bring together bioinformaticians from different fields with designers, design researchers, and medical and scientific illustrators to discuss future challenges in the context of bioinformatics and design.

The aim of this special issue is to provide the readers with a set of reviews that describe the latest concepts, innovations, approaches and technologies in the area of deep learning in bioinformatics, computational biology and systems medicine.

This paper proposes Bio-Informatics Agent (BIA), an intelligent agent leveraging Large Language Models (LLMs) technology, to facilitate autonomous bioinformatic analysis through natural language to demonstrate BIA’s remarkable proficiency in information processing and analysis, as well as executing sophisticated tasks and interactions.

H3ABioNet has created a flexible, sustainable and high quality bioinformatics training environment that has successfully been implemented to train several highly skilled African bioinformaticians on the continent.

This paper aims to design a robust model for diagnosis of diabetes using a hybrid approach of Chaotic-Jaya (CJaya) algorithm with Extreme Learning Machine (ELM), which is named as CJaya-ELM.

This article presents BioDWH2, an open-source, graph-based data warehouse and mapping tool, capable of helping researchers with data integration and mapping issues in biomedical research.

Recent developments in epitranscriptome spatial detection and data analysis are summarized and their progression is discussed.

The bioinformatic discovery of an orphan dinuclear monooxygenase that preferentially utilizes a heterobimetallic manganese–iron (Mn/Fe) cofactor to mediate an O2-dependent C–H bond hydroxylation reaction.

Molecular profiling of tumor biopsies is becoming more and more crucial to both cancer research and the treatment of cancer.

This work has developed bioinformatics workflows for use with Terra that specifically meet the needs of public health practitioners, and these Theiagen workflows perform genome assembly, quality control, and characterization, as well as construction of phylogeny for insights into genomic epidemiology.

It is believed that GNNs are potentially an excellent method that solves various biological problems in bioinformatics research and have a long road ahead.

The paper discusses in more detail the molecular docking problem, the protein structure prediction, phylogenetic inference, and other optimization problems in the area of bioinformatics.

The notion of an approximate hash may be adapted to string processing problems arising in Bioinformatics, and it is shown how the outcome of the new procedure is very similar to the clustering and search results obtained by accurate tools, but in much less time and with less required memory.

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.

This review covers tools for examining gene expression and co-expression patterns, undertaking promoter analyses and gene set enrichment analyses, and exploring protein-protein and protein-DNA interactions.

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 use of such a complexity metric is demonstrated in differentiating codon-noncodon domains in human and bacterial genomes (which constitute a complex system when seen at the scale of observing a DNA sequence made of vast domains of protein molecules).

This review includes a brief introduction to available resources for an investigation covering aspects such as miRNA sequences, target prediction/validation, miRNAs associated with disease, pathway analysis and genetic variants within miRNAAs.

A website platform that provides interactive customizable analysis tools, including various kinds of correlation analyses, pathway enrichment analysis, weighted correlation network analysis, and other common tools and functions, and provides users with rich sources of bioinformatics analysis courses, offering a platform for researchers to share and exchange knowledge.

This study proposed an iterative model to fine-tune instructions for guiding a chatbot in generating code for bioinformatics data analysis tasks and demonstrated the feasibility of the model by applying it to various bioinformatics topics.

The analysis of molecular mechanisms of disease progression challenges the development of bioinformatics tools and omics data integration and this research presents a novel approach to integrate these tools and data into a single integrated system.

This review will provide a comprehensive overview of the essential components of large language models in bioinformatics, spanning genomics, transcriptomics, proteomics, drug discovery, drug discovery, and single-cell analysis.

The development of sparse representation is reviewed, its applications in bioinformatics are explained, namely the use of low-rank representation matrices to identify and study cancer molecules, low- rank sparse representations to analyze and process gene expression profiles, and an introduction to related cancers and gene expression profile database.

The fact that OpenAI ultimately prevailed in this game shows that the model alignment to human labeling through supervised and reinforcement learning is critical for human-machine interaction.

Current and future grand challenges in bioinformatics data visualization are outlined, and the first publication venue dedicated to this subdiscipline is announced.

bit is a collection of small scripts and programs that facilitate many common tasks in bioinformatics. It operates in a Unix-like command-line environment and is comprised of bash and python code. bit is openly available on GitHub, archived with Zenodo, and is conda installable. The package is useful for users who want to do things such as manipulate fasta files, calculate GC content, quickly summarize nucleotide assemblies, easily download assemblies from NCBI just based on accessions, pull amino-acid sequences from GenBank files, calculate Shannon uncertainty for columns in multiple sequence...

This review structures the CC approaches in the literature into three principal types, introduces and illustrates the concept of stability scores, and illustrates the use of CC in applications to simulated and real-world gene expression datasets.

This Perspective sheds light on a wish list for a computational platform to orchestrate benchmark studies, and discusses various ideas for organizing reproducible software environments, formally defining benchmarks, orchestrating standardized workflows, and how they interface with computing infrastructure.

The importance of explainability and algorithmic transparency in the context of bioinformatics is discussed and an overview of model-specific and model-agnostic interpretable ML methods and tools is provided and their potential limitations are outlined.

A general investigation and summary of FMs in bioinformatics, tracing their evolutionary trajectory, current research landscape, and methodological frameworks, and outline prospective pathways and methodologies for the future development of FMs in biological research, facilitating ongoing innovation in the field.

The application of multilayer networks and chronological networks in brain research is described to demonstrate the primary ideas associated with the application ofMultilayers in biological studies and a quality assessment method focusing on multilayers and single-layer networks as an evaluation method emphasizing network studies is mentioned.