Bioinformatics sits at the fascinating intersection of biology, computer science, and data analysis, with Python as a powerful language that drives groundbreaking research and computational discoveries. As biological datasets continue to grow exponentially in complexity and size, researchers and computational biologists increasingly rely on Python’s robust ecosystem of specialized libraries to process genomic data, analyze…
R is a powerful and versatile programming language widely used in biological data analysis for its robust statistical capabilities and extensive library of tools tailored for data visualization, manipulation, and modeling. In the realm of biology, where datasets are often complex and multidimensional, R provides an efficient platform for analyzing genomic sequences, protein structures, ecological…
Artificial intelligence continues advancing into uncharted territory, now claiming the ability to peek into people’s futures. Researchers from the Technical University of Denmark have developed a machine learning algorithm that can predict various life outcomes, like income and mortality risk, based solely on patterns gleaned from Danish national population registers. A recent study in Nature Computational…
Understanding diverse molecular mechanisms is necessary for the research of complex diseases. Using COSMOS, the integration of Thermal Proteome Profiling (TPP) with phosphoproteomics and transcriptomics provides a comprehensive perspective of biological activities. The technique emphasized the importance of TPP in functional proteomics by discovering both well-known and novel molecular responses to Poly (ADP-ribose) polymerases (PARPs)…
Large Language Models (LLMs) have emerged as dynamic tools with the ability to transform the landscape of biological research in a world driven by data and technology. These advanced AI models, including well-known names like BERT and GPT, are not confined to linguistics but have found their way into the complex realm of biology. In…
Genomics to Notebook (g2nb) is a new environment that combines the popular JupyterLab notebook system with well-established bioinformatics platforms to provide a seamless and accessible workflow for genomics analysis. While Jupyter Notebook and JupyterLab have become widely used in data science and bioinformatics, incorporating existing bioinformatics analysis platforms like Galaxy and GenePattern into the notebook…
The Children’s Hospital of Philadelphia (CHOP) scientists have created ESPRESSO, a new computational tool for analyzing RNA-seq data. ESPRESSO aims to improve the detection and quantification of transcript isoforms, which are variations of a gene that can serve different functions. ESPRESSO is particularly useful when dealing with long-read RNA-seq data, which can be prone to…
Recent advancements in trajectory inferences have unfolded a new side of bioinformatics, i.e., single-cell analysis. The research group from the University of Northern Carolina School of Medicine benchmark study addressed gaps in capturing temporal changes in a single-cell state. Interpretation of dynamic phenotypes using ten datasets spanning different biological environments at three distinct temporal stages….
Cancer is a disease that affects millions of people worldwide. According to the World Health Organization (WHO), cancer is the second leading cause of death globally, after cardiovascular diseases. In 2018, about 9.6 million deaths were reported due to cancer. The WHO estimates that over 1.8 million people died from cancer in 2017. The number…
Scientists from the Swiss Institute of Bioinformatics devise a workflow known as Single Cell Analysis mRNA Pipeline, ‘scAmpi,’ for providing complete functionality to scRNA-seq data analysis. In order to understand tissue composition at the single-cell level, to shed light on disease processes, tumor heterogeneity, and the condition of the immune milieu, single-cell RNA sequencing (scRNA-seq) has…
The Chinese Academy of Sciences researchers introduced a dual-plasmid editing system that enhances DNA digital storage. The study strongly encourages the use of DNA-based information technology by demonstrating a digital-to-biological information processing approach for highly effective data storage, amplification, and rewriting. In recent years, DNA has gained increasing attention as an information storage medium. A…
Scientists from the University of Edinburgh developed an open-source platform, ‘Graphia’, for the graph-based visualization and analysis of the high dimensional data being produced from research on cells, genes, proteins, and metabolites. A brand-new visual analytics platform called Graphia was developed especially for network-based analysis of enormous and complicated data, such as the vast volumes…
Scientists from Yale University developed a novel private blockchain network by employing layered database indexing for the storage of reference-aligned next-generation sequencing reads and individual genetic variants. Major initiatives are being made to integrate genome sequencing into clinical practice regularly. Finding workable solutions for data ownership and integrity is a significant hurdle. Blockchain offers answers to…
In order to better prevent and cure debilitating ailments including Alzheimer’s disease, schizophrenia, and autism, new research at Georgia State University’s TReNDS Center may result in early detection. For a recent study published in Nature Scientific Reports, a team of seven scientists from Georgia State University created a sophisticated computer program to sift through enormous…
Scientists from Whitehead Institute and collaborators used Perturb-seq, a single-cell sequencing technology, to link every expressed gene in the human genome to its function in the cell, offering a free resource for other researchers that can be accessed via the internet. The Human Genome Project was a huge undertaking that aimed to sequence every single…
Scientists from Brown University identified the novel usage of FDA-approved drugs by cluster analysis of behavioral profiles for the treatment of neurodegenerative disorders by utilizing CsA-type drugs, which are known to impact the neural system. The study suggests that drugs with ‘CsA-type’ behavioral profiles are potential candidates for preventing and treating Alzheimer’s disease. Repurposing FDA-approved…
In recent years, deep learning algorithms have shown promise in identifying protein function and extracting complex sequence-structure-function correlations. Scientists from Middle East Technical University and Karadeniz Technical University present a benchmarking study that compares the results and benefits of various deep learning algorithms in various protein prediction tasks. The data-centric approaches have been utilized for…
An international group of scientists has finally published the whole human genome sequence. The new reference genome fills in gaps left by previous versions, allowing researchers to understand better genetic variation and how it can contribute to disease in specific cases. The complete human genome sequence has already provided new perspectives to genome biology and…
Scientists from the Center for the Study of Systems Biology, Atlanta, in collaboration with the Georgia Institute of Technology, Atlanta, and Oak Ridge National Laboratory, Oak Ridge, USA, have introduced a new method, ‘AF2complex’, in which AlphaFold2 (AF2) can be used to predict protein complex structure and protein-protein interactions. It is expected to provide significant…
Scientists from Fondazione Poliambulanza Istituto Ospedaliero, Italy, developed a hybrid machine learning/deep learning model to classify patients in two outcome categories, non-ICU, and ICU. With the likelihood score belonging to an outcome class and case-based SHAP interpretation of feature importance, the model intends to give clinical decision support to medical physicians. The scientists devised a…
Variabel, a novel approach and first method designed for rescuing low frequency intra-host variants from Oxford Nanopore Technologies (ONT) data alone. Details about variants hidden in the deluge of genetic SARS-CoV-2 sequences might be helpful if researchers can find them. A new program developed at Rice University’s George R. Brown School of Engineering will make…
A team of international researchers led by the University of California San Diego’s Department of Computer Science and Engineering has demonstrated that the La Jolla Assembler (LJA), a new genome assembly algorithm, vastly improves large genome reconstruction, the process of arranging DNA snippets into complete genomes, which is a crucial part of genomic sequencing. Furthermore,…
New software built by Princeton University researchers may determine whether someone is infected with COVID-19 in minutes by combining questions about a person’s health with data from wristwatch sensors. The study led by Niraj Jha, a professor of electrical and computer engineering at Princeton University, resulted in this new diagnostic tool. His group is working…
Yale scientists report in the journal Nature Biotechnology this week that a novel data analysis technique they created has uncovered the particular immune cell types linked to an elevated risk of mortality from COVID-19. A variety of technologies provide high-throughput biological data by measuring dozens to tens of thousands of features in millions of cells…
Scientists from MIT probed into how proteins recognize and bind to one another, informing drug treatments for cancer. A single cell, despite its small size, has billions of molecules that buzz around and bond to one another, performing critical tasks. About 20,000 proteins are encoded in the human genome, the majority of which interact with…
A team of scientists led by a former University of British Columbia (UBC) postdoctoral researcher in medical genetics discovered over ten times the number of RNA viruses previously thought to exist, including many novel coronavirus species. By re-analyzing all publicly accessible RNA sequencing data, the researchers were able to make the finding. They established a…
Scientists from the Broad Institute of MIT and Harvard discovered an approach to studying the functional implications of the millions of mutations linked to cancer by pooling Perturb-seq and measuring the impact of TP53 and KRAS variants on RNA profiles in single cancer cells. Precision medicine entails predicting how specific genetic variants affect a patient’s…
Scientists from EMBL-EBI, NIH, NHGRI, and collaborators have discovered new micro-organisms (bacterial, fungal species, and viruses) in the human skin microbiome. The human skin microbiome is essential for skin health and illness, and studying its makeup might help us better understand skin-related diseases. Researchers employed metagenomics to create new human skin microbiome reference genomes. Data…
Targeting nucleic acid macromolecules, particularly RNA, for structure-based drug design (SBDD) is gaining research attention as it resulted in several FDA-approved compounds targeting RNA molecules. Scientists from Skoltech’s iMolecule group have created an artificial intelligence-driven approach, “BiteNetN,” to identify sites on the structures of DNA or RNA molecules where drug compounds may bind. The drug-binding…
For data visualization, the spiral arrangement offers two significant advantages. Firstly, data with long axes can be visualized, enhancing visualization resolution. Secondly, time-series data may be used to reveal recurring patterns. spiralize is an R package that offers a generic solution for displaying data on spirals. It has many graphics functions that allow users to…
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