Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Scientific figures interpreted by ChatGPT: strengths in plot recognition and limits in color perception.

ABSTRACT: Emerging studies underscore the promising capabilities of large language model-based chatbots in conducting basic bioinformatics data analyses. The recent feature of accepting image inputs by ChatGPT, also known as GPT-4V(ision), motivated us to explore its efficacy in deciphering bioinformatics scientific figures. Our evaluation with examples in cancer research, including sequencing data analysis, multimodal network-based drug repositioning, and tumor clonal evolution, revealed that ChatGPT can proficiently explain different plot types and apply biological knowledge to enrich interpretations. However, it struggled to provide accurate interpretations when color perception and quantitative analysis of visual elements were involved. Furthermore, while the chatbot can draft figure legends and summarize findings from the figures, stringent proofreading is imperative to ensure the accuracy and reliability of the content.

SUBMITTER: Wang J

PROVIDER: S-EPMC10997760 | biostudies-literature | 2024 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

Scientific figures interpreted by ChatGPT: strengths in plot recognition and limits in color perception.

Wang Jinge J Ye Qing Q Liu Li L Guo Nancy Lan NL Hu Gangqing G

NPJ precision oncology 20240405 1

Emerging studies underscore the promising capabilities of large language model-based chatbots in conducting basic bioinformatics data analyses. The recent feature of accepting image inputs by ChatGPT, also known as GPT-4V(ision), motivated us to explore its efficacy in deciphering bioinformatics scientific figures. Our evaluation with examples in cancer research, including sequencing data analysis, multimodal network-based drug repositioning, and tumor clonal evolution, revealed that ChatGPT can ...[more]

PMID: 38580746

Similar Datasets

Creating clear and informative image-based figures for scientific publications.

Project description:Scientists routinely use images to display data. Readers often examine figures first; therefore, it is important that figures are accessible to a broad audience. Many resources discuss fraudulent image manipulation and technical specifications for image acquisition; however, data on the legibility and interpretability of images are scarce. We systematically examined these factors in non-blot images published in the top 15 journals in 3 fields; plant sciences, cell biology, and physiology (n = 580 papers). Common problems included missing scale bars, misplaced or poorly marked insets, images or labels that were not accessible to colorblind readers, and insufficient explanations of colors, labels, annotations, or the species and tissue or object depicted in the image. Papers that met all good practice criteria examined for all image-based figures were uncommon (physiology 16%, cell biology 12%, plant sciences 2%). We present detailed descriptions and visual examples to help scientists avoid common pitfalls when publishing images. Our recommendations address image magnification, scale information, insets, annotation, and color and may encourage discussion about quality standards for bioimage publishing.

| S-EPMC8041175 | biostudies-literature

A gigabyte interpreted seismic dataset for automatic fault recognition.

Project description:The lack of large-scale open-source expert-labelled seismic datasets is one of the barriers to applying today's AI techniques to automatic fault recognition tasks. The dataset present in this article consists of a large number of processed seismic images and their corresponding fault annotations. The processed seismic images, which are originally from a seismic survey called Thebe Gas Field in the Exmouth Plateau of the Carnarvan Basin on the NW shelf of Australia, are represented in Python Numpy format, which can be easily adopted by various AI models and will facilitate cooperation with researchers in the field of computer science. The corresponding fault annotations were firstly manually labelled by expert interpreters of faults from seismic data in order to investigate the structural style and associated evolution of the basin. Then the fault interpretation and seismic survey are processed and collected using Petrel software and Python programs separately. This dataset can help to train, validate, and evaluate the performance of different automatic fault recognition workflow.

| S-EPMC8220338 | biostudies-literature

Presenting fake figures: a tool to teach effective scientific figure design.

Project description: Not available

| S-EPMC3867769 | biostudies-literature

Automatic target recognition based on cross-plot.

Project description:Automatic target recognition that relies on rapid feature extraction of real-time target from photo-realistic imaging will enable efficient identification of target patterns. To achieve this objective, Cross-plots of binary patterns are explored as potential signatures for the observed target by high-speed capture of the crucial spatial features using minimal computational resources. Target recognition was implemented based on the proposed pattern recognition concept and tested rigorously for its precision and recall performance. We conclude that Cross-plotting is able to produce a digital fingerprint of a target that correlates efficiently and effectively to signatures of patterns having its identity in a target repository.

| S-EPMC3183066 | biostudies-literature

Adapting ChatGPT for Color Blindness in Medical Education.

Project description:Color vision deficiency (CVD) affects a significant portion of the population, yet its impact is often overlooked in medical education, especially in visually demanding specialties like dermatology, pathology, and radiology. In this study, we investigated the potential of ChatGPT to comprehend CVD-simulated images in image-based diagnostic tasks. Notably, the model successfully adapted its diagnostic reasoning to match CVD-modified color perception while preserving high prediction accuracy. These findings highlight the potential of using ChatGPT to foster more inclusive learning environments for individuals with CVD in visually intensive medical specialties.

| S-EPMC11782439 | biostudies-literature

Prof. David L. Schriger: Guidelines for Presenting Tables and Figures in Scientific Manuscripts

Project description: Not available

| S-EPMC9511198 | biostudies-literature

Chromaticity of color perception and object color knowledge.

Project description:Sensorimotor theories of semantic memory require overlap between conceptual and perceptual representations. One source of evidence for such overlap comes from neuroimaging reports of co-activation during memory retrieval and perception; for example, regions involved in color perception (i.e., regions that respond more to colored than grayscale stimuli) are activated by retrieval of object color. One unanswered question from these studies is whether distinctions that are observed during perception are likewise observed during memory retrieval. That is, are regions defined by a chromaticity effect in perception similarly modulated by the chromaticity of remembered objects (e.g., lemons more than coal)? Subjects performed color perception and color retrieval tasks while undergoing fMRI. We observed increased activation during both perception and memory retrieval of chromatic compared to achromatic stimuli in overlapping areas of the left lingual gyrus, but not in dorsal or anterior regions activated during color perception. These results support sensorimotor theories but suggest important distinctions within the conceptual system.

| S-EPMC3261614 | biostudies-literature

PHY.FI: fast and easy online creation and manipulation of phylogeny color figures.

Project description:BackgroundThe need to depict a phylogeny, or some other kind of abstract tree, is very frequently experienced by researchers from a broad range of biological and computational disciplines. Thousands of papers and talks include phylogeny figures, and often during everyday work, one would like to quickly get a graphical display of, e.g., the phylogenetic relationship between a set of sequences as calculated by an alignment program such as ClustalW or the phylogenetic package Phylip. A wealth of software tools capable of tree drawing exists; most are comprehensive packages that also perform various types of analysis, and hence they are available only for download and installing. Some online tools exist, too.ResultsThis paper presents an online tool, PHY.FI, which encompasses all the qualities of existing online programs and adds functionality to hopefully eliminate the need for post-processing the phylogeny figure in some other general-purpose graphics program. PHY.FI is versatile, easy-to-use and fast, and supports comprehensive graphical control, several download image formats, and the possibility of dynamically collapsing groups of nodes into named subtrees (e.g. "Primates"). The user can create a color figure from any phylogeny, or other kind of tree, represented in the widely used parenthesized Newick format.ConclusionPHY.FI is fast and easy to use, yet still offers full color control, tree manipulation, and several image formats. It does not require any downloading and installing, and thus any internet user regardless of computer skills, and computer platform, can benefit from it. PHY.FI is free for all and is available from this web address: http://cgi-www.daimi.au.dk/cgi-chili/phyfi/go.

| S-EPMC1513607 | biostudies-literature

QuickFigures: A toolkit and ImageJ PlugIn to quickly transform microscope images into scientific figures.

Project description:Publications involving fluorescent microscopy images generally contain many panels with split channels, merged images, scale bars and label text. Similar layouts of panels are used when displaying other microscopy images, electron micrographs, photographs, and other images. Assembling and editing these figures with even spacing, consistent font, text position, accurate scale bars, and other features can be tedious and time consuming. In order to save time, I have created a toolset and ImageJ Plugin called QuickFigures. QuickFigures includes many helpful features that streamline the process of creating, aligning, and editing scientific figures. Those features include tools that automatically create split channel figures from a region of interest ("Quick Figure" button and "Inset Tool"), layouts that make it easy to rearrange panels, multiple tools to align objects, and "Figure Format" menu options that help a user ensure that large numbers of figures have consistent appearance. QuickFigures was compared to previous tools by measuring the amount of time needed for a user to create a figure using each software (QuickFigures, OMERO.figure. EZFig, FigureJ and PowerPoint). QuickFigures significantly reduced the amount of time required to create a figure. The toolsets were also compared by checking each software against a list of features. QuickFigures had the most extensive set of features. Therefore, QuickFigures is an advantageous alternative to traditional methods of constructing scientific figures. After a user has saved time by creating their work in QuickFigures, the figures can be exported to a variety of formats including PowerPoint, PDF, SVG, PNG, TIFF and Adobe Illustrator. Export was successfully tested for each file format and object type. Exported objects and text are editable in their target software, making them suitable for sharing with collaborators. The software is free, open source and can be installed easily.

| S-EPMC8577749 | biostudies-literature

Embedding and publishing interactive, 3-dimensional, scientific figures in Portable Document Format (PDF) files.

Project description:With the latest release of the S2PLOT graphics library, embedding interactive, 3-dimensional (3-d) scientific figures in Adobe Portable Document Format (PDF) files is simple, and can be accomplished without commercial software. In this paper, we motivate the need for embedding 3-d figures in scholarly articles. We explain how 3-d figures can be created using the S2PLOT graphics library, exported to Product Representation Compact (PRC) format, and included as fully interactive, 3-d figures in PDF files using the movie15 LaTeX package. We present new examples of 3-d PDF figures, explain how they have been made, validate them, and comment on their advantages over traditional, static 2-dimensional (2-d) figures. With the judicious use of 3-d rather than 2-d figures, scientists can now publish, share and archive more useful, flexible and faithful representations of their study outcomes. The article you are reading does not have embedded 3-d figures. The full paper, with embedded 3-d figures, is recommended and is available as a supplementary download from PLoS ONE (File S2).

| S-EPMC3783416 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data