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At least 235 records · Page 13Linked to original sources

PubMed2025

FuNTB: a functional network clustering tool for the analysis of genome-wide genetic variants in Mycobacterium tuberculosis.

MOTIVATION: Tuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb), still claims around 1.25 million lives each year. The growing threat of drug resistance-often driven by single‑nucleotide polymorphisms (SNPs) in Mtb genomes underscores the need for high‑quality genomic data and powerful bioinformatics tools. We present FuNTB, a python‑based pipeline that detects non‑synonymous SNPs in Mtb and builds functional network clusters to reveal genotype-phenotype relationships. RESULTS: FuNTB profiles non‑synonymous SNPs at the gene level across user‑defined phenotypes, pinpointing both shared and unique mutations. It ingests annotated Variant Call Format (VCF) files or MTBseq outputs and merges them with clinical metadata to produce network‑XML files compatible with Cytoscape and Gephi. When applied to the CRyPTIC Mtb collection, FuNTB rapidly recovered established resistance genes and surfaced novel candidates, validating its utility for mapping genotype-phenotype associations. AVAILABILITY AND IMPLEMENTATION: FuNTB is implemented in Python 3.8+ and is freely available under the MIT license at https://doi.org/10.5281/zenodo.15399917.

Mycobacterium tuberculosis↗

PubMed2025

Fast and flexible minimizer digestion with digest.

SUMMARY: Minimizer digestion is an increasingly common component of bioinformatics tools, including tools for de Bruijn graph assembly and sequence classification. We describe a new open source tool and library to facilitate efficient digestion of genomic sequences. It can produce digests based on the related ideas of minimizers, modimizers or syncmers. Digest uses efficient data structures, scales well to many threads, and produces digests with expected spacings between digested elements. AVAILABILITY AND IMPLEMENTATION: Digest is implemented in C++17 with a Python API, and is available open-source at https://github.com/VeryAmazed/digest. The python library is available on Bioconda. Rust bindings are available as a public crate at https://crates.io/crates/digest-rs.

Software↗

PubMed2025

Tsbrowse: an interactive browser for ancestral recombination graphs.

SUMMARY: Ancestral recombination graphs (ARGs) represent the interwoven paths of genetic ancestry of a set of recombining sequences. The ability to capture the evolutionary history of samples makes ARGs valuable in a wide range of applications in population and statistical genetics. ARG-based approaches are increasingly becoming a part of genetic data analysis pipelines due to breakthroughs enabling ARG inference at biobank-scale. However, there is a lack of visualization tools, which are crucial for validating inferences and generating hypotheses. We present tsbrowse, an open-source, web-based Python application for the interactive visualization of the fundamental building blocks of ARGs, i.e. nodes, edges and mutations. We demonstrate the application of tsbrowse to various data sources and scenarios, and highlight its key features of browsability along the genome, user interactivity, and scalability to very large sample sizes. AVAILABILITY AND IMPLEMENTATION: Tsbrowse is installed as a Python package from PyPI (https://pypi.org/project/tsbrowse/), while a development version is maintained at https://github.com/tskit-dev/tsbrowse. Documentation is available at https://tskit.dev/tsbrowse/docs/. Source code is archived on Zenodo with DOI, https://doi.org/10.5281/zenodo.15683039.

Software↗

PubMed2025

ShortCake: an integrated platform for efficient and reproducible single-cell analysis.

SUMMARY: Recent advances in single-cell analysis have introduced new computational challenges. Researchers often need to use multiple analysis tools written in different programming languages while managing version conflicts between related packages within a single workflow. For the research community, minimizing the time spent on environment setup and installation issues is essential. We present ShortCake, a containerized platform that integrates a suite of single-cell analysis tools written in R and Python. ShortCake isolates competing Python tools into separate virtual environments that can be easily accessed within a Jupyter notebook. This enables users to effortlessly transition between various environments, including R, even within a single notebook. Additionally, ShortCake offers multiple "flavors," enabling users to select container images tailored to their specific needs. ShortCake provides a unified environment with fixed versions of various tools, thus streamlining workflows, reducing setup time, and improving reproducibility. AVAILABILITY AND IMPLEMENTATION: The ShortCake image is available on DockerHub (https://hub.docker.com/r/rnakato/shortcake) and Zenodo (DOIs: 10.5281/zenodo.17116765 and 10.5281/zenodo.17118158). The source code is available on GitHub (https://github.com/rnakato/ShortCake).

Single-Cell Analysis↗

PubMed2025

Tomtom-lite: accelerating Tomtom enables large-scale and real-time motif similarity scoring.

SUMMARY: Pairwise sequence similarity is a core operation in genomic analysis, yet most attention has been given to sequences made up of discrete characters. With the growing prevalence of machine learning, calculating similarities for sequences of continuous representations, e.g. frequency-based position-weight matrices (PWMs) and attribution-based contribution-weight matrices, is taking on newfound importance. Tomtom has previously been proposed as an algorithm for identifying pairs of PWMs whose similarity is statistically significant, but the implementation remains inefficient for both real-time and large-scale analysis. Accordingly, we have re-implemented Tomtom as a numba-accelerated Python function that is natively multi-threaded, avoids cache misses, more efficiently caches intermediate values, and uses approximations at compute bottlenecks. Here, we provide a detailed description of the original Tomtom method and present results demonstrating that our re-implementation can achieve over a 1000-fold speedup compared with the original tool on reasonable tasks. AVAILABILITY AND IMPLEMENTATION: Our implementation of Tomtom is freely available as a Python package at https://github.com/jmschrei/memesuite-lite, which can be downloaded via pip install memelite or at https://zenodo.org/records/17008952.

Software↗

PubMed2026

DNAvi: integration, statistics, and visualization of cell-free DNA fragment traces.

SUMMARY: DNAvi is a Python-based tool for rapid grouped analysis and visualization of cell-free DNA fragment size profiles directly from electrophoresis data, overcoming the need for sequencing in basic fragmentomic screenings. It enables normalization, statistical comparison, and publication-ready plotting of multiple samples, supporting quality control and exploratory fragmentomics in clinical and research workflows. AVAILABILITY AND IMPLEMENTATION: DNAvi is implemented in Python and freely available on GitHub at https://github.com/anjahess/DNAvi under a GNU General Public License v3.0, along with source code, documentation, and examples. An archived version is available under https://doi.org/10.5281/zenodo.18401705.

Software↗

PubMed2026

ORFannotate: reproducible coding sequence annotation of transcriptome assemblies.

SUMMARY: Accurate annotation of coding sequences and translational features within transcript models is essential for interpreting assembled transcriptomes and their functional potential. Existing open reading frame (ORF) prediction tools typically operate on transcript FASTA files and do not reintegrate coding sequence (CDS) information back into transcript models, limiting their utility in long-read sequencing workflows where GTF/GFF annotations are the primary output. We present ORFannotate, a lightweight, GTF-native Python command-line tool that predicts ORFs from transcript annotations and reinserts precise, exon-aware CDS and UTR features into the original GTF/GFF file. In addition, ORFannotate provides biologically informative translational context by annotating Kozak sequence strength, detecting non-overlapping upstream ORFs (uORFs) with coding probabilities, characterising 5' and 3' untranslated regions (UTRs), and predicting nonsense-mediated decay (NMD) susceptibility. All annotations are consolidated in a transcript-level summary to support downstream analysis. By generating GTF files with accurate CDS annotations, ORFannotate facilitates reproducible analysis of both long- and short-read transcriptomes and integrates seamlessly with visualization tools, genome browsers, and comparative transcript analysis workflows. ORFannotate is fast, scalable and provides a practical solution for transcriptome annotation beyond coding potential prediction alone. AVAILABILITY AND IMPLEMENTATION: ORFannotate is implemented in Python and freely available under the GNU General Public License v3 (GPL-3.0) at: https://github.com/egustavsson/ORFannotate (DOI: https://doi.org/10.5281/zenodo.16812866).

Open Reading Frames↗

PubMed2026

ssHiCstuff: a package for the design and analysis of ssDNA-specific Hi-C experiments.

MOTIVATION: Single-strand DNA-specific Hi-C (ssHi-C) is a recently developed technique enabling the capture of chromatin interactions involving single-stranded DNA (ssDNA), an intermediate of various DNA metabolic processes. ssHi-C entails the restoration of restriction sites in ssDNA regions of interest upon introduction of designer, internally barcoded "annealing oligonucleotides" prior to the restriction digestion step of Hi-C. The design of these "annealing oligonucleotides," as well as the analysis of the resulting ssHi-C data presents specific challenges, such as (i) differentiating ssDNA from dsDNA-derived contacts, (ii) tracking probe-specific interactions, and (iii) calibrating the amount of ssDNA contacts across biological samples. Dedicated computational tools are therefore needed to facilitate the design of, and extract biological information from, ssHi-C experiments. RESULTS: We present ssHiCstuff, a Rust- and Python-based package for the design of key reagents for ssHi-C experiments and for the analysis of ssHi-C data. ssHiCstuff provides (i) an automated annealing oligonucleotides design module, (ii) an end-to-end analyses pipeline, and (iii) a graphical user interface. ssHiCstuff simplifies the high-resolution analysis of ssDNA interactions at genome-wide scale. A graphical user interface (GUI) implemented in Python is also available for biologists without coding skills. AVAILABILITY: ssHiCstuff is freely available at https://github.com/Piazzalab/ssHiCstuff and https://zenodo.org/records/19677479 (https://doi.org/10.5281/zenodo.19677479) under the GPL 3.0 license. The annealing oligonucleotides design and the visualization modules are additionally freely available on a web browser at https://bioshiny.ens-lyon.fr/public/app/sshicstuff. A test dataset is available at https://zenodo.org/records/20035366 (https://doi.org/10.5281/zenodo.20035366).

DNA, Single-Stranded↗

PubMed2026

Plotgardener App: a graphical interface for publication-ready genomic visualization.

SUMMARY: Plotgardener is an R package used for generating high-quality genomic visualizations. Despite its broad range of functions and versatility, its reliance on code presents a barrier for many potential users. To address this, we developed a macOS desktop application version of Plotgardener that enables users to create publication-ready genomic plots with no programming experience. The application employs a modular architecture comprising an Electron.js backend, a React frontend, and a Python parser that dynamically analyzes the Plotgardener package to ensure interface fields remain synchronized with package updates. By lowering the technical barrier to advanced genomic visualization, the Plotgardener desktop application broadens access to powerful visualization workflows for researchers and clinicians. AVAILABILITY: The current release of the Plotgardener App is an open source macOS desktop application built with Electron (Node.js), featuring a React frontend and a Python-based parser. The download link is available at https://phanstiellab.github.io/plotgardener/articles/guides/plotgardenerApp.html and on Zenodo (doi: https://doi.org/10.5281/zenodo.21684228). The source code is hosted on GitHub at https://github.com/rishabhsvemuri/ThePlotgardenerApp.

Genomics↗

PubMed2005

PROVAT: a tool for Voronoi tessellation analysis of protein structures and complexes.

SUMMARY: Voronoi tessellation has proved to be a useful tool in protein structure analysis. We have developed PROVAT, a versatile public domain software that enables computation and visualization of Voronoi tessellations of proteins and protein complexes. It is a set of Python scripts that integrate freely available specialized software (Qhull, Pymol etc.) into a pipeline. The calculation component of the tool computes Voronoi tessellation of a given protein system in a way described by a user-supplied XML recipe and stores resulting neighbourhood information as text files with various styles. The Python pickle file generated in the process is used by the visualization component, a Pymol plug-in, that offers a GUI to explore the tessellation visually. AVAILABILITY: PROVAT source code can be downloaded from http://raven.bioc.cam.ac.uk/~swanand/Provat1, which also provides a webserver for its calculation component, documentation and examples.

Algorithms↗

PubMed2005

ConFind: a robust tool for conserved sequence identification.

SUMMARY: ConFind (conserved region finder) identifies regions of conservation in multiple sequence alignments that can serve as diagnostic targets. Designed to work with a large number of closely related, highly variable sequences, ConFind provides robust handling of alignments containing partial sequences and ambiguous characters. Conserved regions are defined in terms of minimum region length, maximum informational entropy (variability) per position, number of exceptions allowed to the maximum entropy criterion and the minimum number of sequences that must contain a non-ambiguous character at a position to be considered for inclusion in a conserved region. Comparison of the calculated entropy for an alignment of 95 influenza A hemagglutinin sequences with random deletions results in a 98% reduction in the average error in ConFind relative to the 'Find Conserved Regions' option in BioEdit. REQUIREMENTS: ConFind requires Python 2.3, but Python 2.4 or an upgrade of the optparse module to Optik 1.5 is suggested. The program is known to run under Linux and DOS.

Algorithms↗

PubMed2025

MyESL: A Software for Evolutionary Sparse Learning in Molecular Phylogenetics and Genomics.

Evolutionary sparse learning uses supervised machine learning to build evolutionary models where genomic sites loci are parameters. It uses the Least Absolute Shrinkage and Selection Operator with bi-level sparsity to connect a specific phylogenetic hypothesis with sequence variation across genomic loci. The MyESL software addresses the need for open-source tools to perform evolutionary sparse learning analyses, offering features to preprocess input phylogenomic alignments, post-process output models to generate molecular evolutionary metrics, and make Least Absolute Shrinkage and Selection Operator regression adaptable and efficient for phylogenetic trees and alignments. The core of MyESL, which constructs models with logistic regressions using bi-level sparsity, is written in C++. Its input data preprocessing and result post-processing tools are developed in Python. Compared to other tools, MyESL is more computationally efficient and provides evolution-friendly inputs and outputs. These features have already enabled the use of MyESL in two phylogenomic applications, one to identify outlier sequences and fragile clades in inferred phylogenies and another to build genetic models of convergent traits. In addition to the use in a Python environment, MyESL is available as a standalone executable compatible across multiple platforms, which can be directly integrated into scripts and third-party software. The source code, executable, and documentation for MyESL are openly accessible at https://github.com/kumarlabgit/MyESL.

Phylogeny↗

PubMed2004

Independent effects of heart-head distance and caudal blood pooling on blood pressure regulation in aquatic and terrestrial snakes.

Changes in orientation in a gravitational field markedly alter the patterns of blood pressure and flow in animals, especially tall or long ones such as giraffes or snakes. Vertical orientation tends to reduce blood flow and pressure in the head for two major reasons. First, the increased vertical blood column above the heart creates a gravitational hydrostatic pressure against which the heart must work. Second, expansion of dependent vessels in the lower extremities causes blood pooling and reduces return of venous blood to the heart, thereby lowering flow and pressure. For most animals, it is difficult to separate these two effects, but snakes offer the possibility of bending the animal in the region of the heart and manipulating the two ends of the body independently. We studied baroregulatory responses in terrestrial pythons (Liasis fuscus) and aquatic file snakes (Acrochordus arafurae) by tilting only the front or rear parts and then the whole animal. Changes in head blood pressure during partial tilts added up to the change during full tilt. The vertical distance to the head had twice as much influence on head blood pressure than did blood pooling in the pythons and four times as much in file snakes. This accounts for the cephalad location of the heart in terrestrial species compared with aquatic ones.

Animals↗

PubMed2006

Parasites of domestic and wild animals in South Africa. XLVII. Ticks of tortoises and other reptiles.

A total of 586 reptiles, belonging to 35 species and five subspecies, were examined in surveys aimed at determining the species spectrum and geographic distribution of ticks that infest them. Of these reptiles 509 were tortoises, 28 monitor or other lizards, and 49 snakes. Nine ixodid tick species, of which seven belonged to the genus Amblyomma, and one argasid tick, Ornithodoros compactus were recovered. Seven of the ten tick species are parasites of reptiles. Amongst these seven species Amblyomma marmoreum was most prevalent and numerous on leopard tortoises, Geochelone pardalis; Amblyomma nuttalliwas present only on Bell's hinged tortoises, Kinixys belliana; and most Amblyomma sylvaticum were collected from angulate tortoises, Chersina angulata. Amblyomma exornatum (formerly Aponomma exornatum) was only recovered from monitor lizards, Varanus spp.; most Amblyomma latum (formerly Aponomma latum) were from snakes; and a single nymph of Amblyomma transversale (formerly Aponomma transversale) was collected from a southern African python, Python natalensis. All 30 Namaqualand speckled padloper tortoises, Homopus signatus signatus, examined were infested with O. compactus. The seasonal occurrence of A. sylvaticum and the geographic distribution of this tick and of A. marmoreum, A. nuttalli, A. exornatum, A. latum and O. compactus are illustrated.

Animals↗

PubMed1999

Pentastomes (Pentastomida, Armillifer armillatus Wyman, 1848) in snakes from Zambia.

Twenty-three snakes, belonging to eight different species, were collected from rural areas of Zambia and inspected for the presence of pentastomes. Pentastomid parasites were found in four snakes: one African rock python (Python sebae), one puff adder (Bitis arietans) and two Mozambique spitting cobras (Naja mossambica) were infested with a small number of Armillifer armillatus, respectively five, two and one adult parasites. As humans can be incidental/intermediate hosts for reptilian pentastomes, the zoonotic potential of these parasites, especially in tropical countries, is discussed.

Animals↗

PubMed1989

[A histological study of striated muscle and nerve fiber in the human caused by a high voltage electric current].

A case of an electrocution is reported, involving a 37-year-old man who while engaged in an electrical work, received an electric shock by touching an electric wire of 11,000 volts. Both of his arms had to be amputated. A piece of muscle tissue was removed from the amputated arm to be examined by light and electron microscopy. Under light microscopy, the muscle tissue, after myoglobin staining, showed a particular pattern that closely resembled the pattern on the skin of a python. Thus the author has named the pattern seen in this case as the "Python-pattern". The electron microscopy inspection revealed on myoglobin staining excessive stretching and fragmentation of the myofibrils where the myoglobin staining was negative in the slide.

Adult↗

PubMed1989

Death caused by a constricting snake--an infant death.

A 21-month-old male was found dead in his crib. An escaped pet python snake (Python reticulatus) was found near the child on a cribside shelf. Autopsy findings included petechiae associated with asphyxial death plus puncture wounds consistent with the reptile's teeth. This report details this 1982 death of a child in Reno, Nevada, and includes illustration of the reptile's bite marks plus description of snake jaw mechanics in swallowing.

Animals↗

PubMed1985

Disease patterns in the Detroit Zoo: a study of reptilian and amphibian populations from 1973 through 1983.

A retrospective study was conducted to determine disease patterns in reptilian and amphibian populations at the Detroit Zoo from 1973 through 1983. In the reptilian population (mean +/- SD = 285.2 +/- 28), overall annual mortality rates were 1% to 40%. Mortality rates were highest in the fall months (20%) and lowest in the winter months (6%). The most frequently affected reptiles were iguana (Iguana iguana), reticulated python (Python reticulatus), rattlesnakes (Crotalus spp), common boa (Constrictor constrictor), and lizards (various genera of suborder Lacertilia). Of the 1,300 reptilian deaths from 1973 through 1983, 36.6% were caused by microbial agents, 12% by parasites, 11.6% by trauma, and 9.3% by nutritional deficiencies. The main microbial organisms that caused death were Aeromonas spp, Salmonella spp, Pseudomonas spp, Proteus spp, and Edwardsiella spp. The main parasites that caused death were Entamoeba spp and lungworms. Among amphibians, frogs and toads were the most frequently affected, and starvation and trauma were the most frequent causes of death.

Amphibians↗