Biology subjects

Gold, I.

Publications and source records attributed to Gold, I..

6 recordsLinked to original sources

bioRxiv2026

Scientific computing in the age of agentic AI: an exploratory field report

Scientific computing has become a central component of modern scientific discovery. Yet many computational tools are developed by small, specialized teams under incentives that encourage the release of rapidly prototyped tooling without commensurate attention to engineering concerns, including performance and maintainability. These gaps are particularly visible in the life sciences, where the advent of high-throughput sequencing and molecular profiling has made the production and processing of datasets routine at scales that strain reliability and cost. Recently, LLM-based agents have become increasingly capable, with publicly available systems possessing both significant domain knowledge in many scientific fields and the ability to autonomously operate over complex and specialized codebases in pursuit of well-defined goals. Together, these developments create a practical opportunity for scientific computing. Many of the persistent weaknesses of the scientific computing ecosystem stem from technical debt and a shortage of sustained engineering labor and expertise. Here, we examine coding agents as a potential way to address these weaknesses: we present an exploratory field report of eight early case studies in the application of LLM agents to scientific computing across a range of project scopes, from lightweight maintenance tasks to full performance-oriented rewrites of scientific libraries, with a focus on the life sciences. Each of these case studies is accompanied by reflections from the individual or group responsible for the work, including lessons from the process. Overall, we find that the use of coding agents in scientific computing holds great promise for accelerating scientific research and increasing the reliability of critical systems, but that outstanding concerns remain, including responsibility and ownership for such projects, and we suggest collaboration and stewardship with existing maintainers when feasible.

bioinformatics↗

bioRxiv2024

Pertpy: an end-to-end framework for perturbation analysis

Advances in single-cell technology have enabled the measurement of cell-resolved molecular states across a variety of cell lines and tissues under a plethora of genetic, chemical, environmental, or disease perturbations. Current methods focus on differential comparison or are specific to a particular task in a multi-condition setting with purely statistical perspectives. The quickly growing number, size, and complexity of such studies requires a scalable analysis framework that takes existing biological context into account. Here, we present pertpy, a Python-based modular framework for the analysis of large-scale perturbation single-cell experiments. Pertpy provides access to harmonized perturbation datasets and metadata databases along with numerous fast and user-friendly implementations of both established and novel methods such as automatic metadata annotation or perturbation distances to efficiently analyze perturbation data. As part of the scverse ecosystem, pertpy interoperates with existing libraries for the analysis of single-cell data and is designed to be easily extended.

bioinformatics↗

bioRxiv2024

A novel functional gene delivery platform based on a commensal human anellovirus demonstrates transduction in multiple tissue types

Anelloviridae is a family of non-enveloped viruses with negative-sense, circular, single-stranded deoxyribonucleic acid (ssDNA) genomes that infect vertebrates and are a ubiquitous component of the human virome. Human anelloviruses evade induction of humoral immune responses and appear to be non-pathogenic. These properties, in conjunction with their enormous genomic diversity and wide tissue distribution, make anelloviruses compelling candidates as vectors for next-generation genetic medicines. Here we report the first gene delivery vector system based on a human commensal virus. This Anellovector is based on a virus of the Betatorquevirus genus. Production is enabled by the development of the Self-Amplifying Trans-complementation of a Universal Recombinant aNellovector (SATURN) system, which relies on a self-replicating plasmid to provide viral proteins in trans that drive replication and capsid-dependent packaging of vector genomes. The SATURN system also utilizes a Cre-lox-based recombination mechanism to generate single unit-sized circular genomes inside the MOLT-4 production cell line. We demonstrate that the SATURN system can package a vector genome from a single betatorquevirus with capsids from multiple betatorquevirus species, supporting the feasibility of establishing a novel vector platform that takes advantage of the remarkable diversity of anelloviruses. The Anellovector demonstrated function in vitro in retinal pigment epithelial (RPE) cells. The Anellovector also demonstrated durable in vivo function in the mouse eye for 9 months after subretinal administration, and achieved comparable gene expression to dose-matched adeno-associated virus 9 (AAV9) when transduced by the intracerebroventricular (ICV) route of administration. To our knowledge, this is the first report of a functional anellovirus-based gene therapy vector. Anellovectors have great potential to deliver safe, redosable, and potent therapeutics, helping to expand the reach of programmable medicines.

bioengineering↗

bioRxiv2023

OME-Zarr: a cloud-optimized bioimaging file format with international community support

A growing community is constructing a next-generation file format (NGFF) for bioimaging to overcome problems of scalability and heterogeneity. Organized by the Open Microscopy Environment (OME), individuals and institutes across diverse modalities facing these problems have designed a format specification process (OME-NGFF) to address these needs. This paper brings together a wide range of those community members to describe the cloud-optimized format itself - OME-Zarr - along with tools and data resources available today to increase FAIR access and remove barriers in the scientific process. The current momentum offers an opportunity to unify a key component of the bioimaging domain -- the file format that underlies so many personal, institutional, and global data management and analysis tasks.

bioinformatics↗

bioRxiv2019

Temporal processing of facial expressions of mental states

Faces provide not only cues to an individuals identity, age, gender and ethnicity, but also insight into their mental states. The ability to identify the mental states of others is known as Theory of Mind. Here we present results from a study aimed at extending our understanding of differences in the temporal dynamics of the recognition of expressions beyond the basic emotions at short presentation times ranging from 12.5 to 100 ms. We measured the effect of variations in presentation time on identification accuracy for 36 different facial expressions of mental states based on the Reading the Mind in the Eyes test (Baron-Cohen et al., 2001) and compared these results to those for corresponding stimuli from the McGill Face database, a new set of images depicting mental states portrayed by professional actors. Our results show that subjects are able to identify facial expressions of complex mental states at very brief presentation times. The kind of cognition involved in the correct identification of facial expressions of complex mental states at very short presentation times suggests a fast, automatic Type-1 cognition.

animal behavior and cognition↗

bioRxiv2019

The McGill Face Database: validation and insights into the recognition of facial expressions of complex mental states

Current databases of facial expressions of mental states typically represent only a small subset of expressions, usually covering the basic emotions (fear, disgust, surprise, happiness, sadness, and anger). To overcome these limitations, we introduce a new database of pictures of facial expressions reflecting the richness of mental states. 93 expressions of mental states were interpreted by two professional actors and high-quality pictures were taken under controlled conditions in front and side view. The database was validated with two different experiments (N=65). First, a four-alternative forced choice paradigm was employed to test the ability of participants to correctly select a term associated with each expression. In a second experiment, we employed a paradigm that did not rely on any semantic information. The task was to locate each face within a two-dimensional space of valence and arousal (mental state - space) employing a \"point-and-click\" paradigm. Results from both experiments demonstrate that subjects can reliably recognize a great diversity of emotional states from facial expressions. Interestingly, while subjects performance was better for front view images, the advantage over the side view was not dramatic. To our knowledge, this is the first demonstration of the high degree of accuracy human viewers exhibit when identifying complex mental states from only partially visible facial features. The McGill Face Database provides a wide range of facial expressions that can be linked to mental state terms and can be accurately characterized in terms of arousal and valence.

animal behavior and cognition↗