Biology subjects

Telmer, C. A.

Publications and source records attributed to Telmer, C. A..

5 recordsLinked to original sources

bioRxiv2024

Context-driven interaction retrieval and classification for modeling, curation, and reuse

Automated extraction of molecular interactions from scientific literature has outpaced the development of systematic methods for integrating this information with curated models and knowledge graphs. Here we present VIOLIN (Versatile Interaction Organizing to Leverage Information in Networks), a configurable, attribute-aware reconciliation framework that formally compares newly extracted interaction lists against structured baseline graphs. VIOLIN classifies each interaction as a corroboration, contradiction, flagged case, or extension, and supports configurable attribute inclusion strategies and mismatch semantics to adjust reconciliation strictness. We evaluate VIOLIN using interaction lists generated by two traditional NLP systems (REACH, INDRA) and two large language models (GPT-4.1, Llama 3) across multiple literature corpora and structurally distinct baseline graphs. Across all conditions, reconciliation outcomes were stable and interpretable, with extensions dominating and corroboration-contradiction balance reflecting intrinsic structural relationships between baseline graphs and extracted evidence. Sensitivity analyses demonstrate that attribute inclusion and classification scheme selection shift category boundaries predictably. Benchmark evaluations confirm high algorithmic correctness and alignment with expert curation. VIOLIN is publicly available as a Python package and through web-based interface (https://nmzlab.github.io/Tools-UI).

systems biology↗

bioRxiv2024

The BioRECIPE Knowledge Representation Format

AO_SCPLOWBSTRACTC_SCPLOWThe BioRECIPE (Biological system Representation for Evaluation, Curation, Interoperability, Preserving, and Execution) knowledge representation format was introduced to facilitate seamless human-machine interaction while creating, verifying, evaluating, curating, and expanding executable models of intra- and intercellular signaling. This format allows a human user to easily preview and modify any model component, while it is at the same time readable by machines and can be processed by a suite of model development and analysis tools. The BioRECIPE format is compatible with multiple representation formats, natural language processing tools, modeling tools, and databases that are used by the systems biology community. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=117 SRC="FIGDIR/small/579694v1_ufig1.gif" ALT="Figure 1"> View larger version (38K): org.highwire.dtl.DTLVardef@76a130org.highwire.dtl.DTLVardef@505cb4org.highwire.dtl.DTLVardef@1f64e68org.highwire.dtl.DTLVardef@195bd03_HPS_FORMAT_FIGEXP M_FIG C_FIG

systems biology↗

bioRxiv2022

New hypotheses of cell type diversity and novelty from comparative single cell and nuclei transcriptomics in echinoderms

Cell types are the fundamental building blocks of metazoan biodiversity and offer a powerful perspective for inferring evolutionary phenomena. With the development of single-cell transcriptomic techniques, new definitions of cell types are emerging. This allows a conceptual reassessment of traditional definitions of novel cell types and their evolution. Research in echinoderms, particularly sea star and sea urchin embryos have contributed significantly to understanding the evolution of novel cell types, in particular the primary mesenchyme cells (PMCs) and pigment cells that are found in sea urchin but not sea star embryos. This paper outlines the development of a gene expression atlas for the bat star, Patiria miniata, using single nuclear RNA sequencing (snRNA-seq) of embryonic stages. The atlas revealed 22 cell clusters covering all expected cell types from the endoderm, mesoderm and ectoderm germ layers. In particular, four distinct neural clusters, an immune cluster, and distinct right and left coelom clusters were revealed as distinct cell states. A comparison with Strongylocentrotus purpuratus embryo single cell transcriptomes was performed using 1:1 orthologs to anchor and then compare gene expression patterns. S. purpuratus primordial germ cell equivalents were not detected in P. minata, while the left coelom of P. miniata has no equivalent cell cluster in S. purpuratus. Pigment cells of S. purpuratus map to clusters containing immune mesenchyme and neural cells of P. miniata, while the PMCs of S. purpuratus are revealed as orthologous to the right coelom cluster of P. miniata. These results suggest a new interpretation of the evolution of these well-studied cell types and a reflection on the definition of novel cell types.

evolutionary biology↗

bioRxiv2021

Computational modeling of cell signaling and mutations in pancreatic cancer

Published research articles are rich sources of data when the knowledge is incorporated into models. Complex biological systems benefit from computational modelings ability to elucidate dynamics, explain data and address hypotheses. Modeling of pancreatic cancer could guide treatment of this devastating disease that has a known mutational profile disrupting signaling pathways but no reliable therapies. The approach described here is to utilize discrete modeling of the major signaling pathways, metabolism and the tumor microenvironment including macrophages. This modeling approach allows for abstraction in order to assemble large networks to capture numerous facets of the biological system under investigation. The Hallmarks of Cancer are represented as the processes of apoptosis, autophagy, cell cycle progression, inflammation, immune response, oxidative phosphorylation and proliferation. The model is initialized with pancreatic cancer receptors and mutations and simulated in time. The model portrays the hallmarks of cancer and suggests combinations of inhibitors as therapies.

systems biology↗

bioRxiv2018

Quantitative synapse analysis for cell-type specific connectomics

Anatomical methods for determining cell-type specific connectivity are essential to inspire and constrain our understanding of neural circuit function. We developed new genetically-encoded reagents for fluorescence-synapse labeling and connectivity analysis in brain tissue, using a fluorogen-activating protein (FAP)-or YFP-coupled, postsynaptically-localized neuroligin-1 targeting sequence (FAP/YFPpost). Sparse viral expression of FAP/YFPpost with the cell-filling, red fluorophore dTomato (dTom) enabled high-throughput, compartment-specific localization of synapses across diverse neuron types in mouse somatosensory cortex. High-resolution confocal image stacks of virally-transduced neurons were used for 3D reconstructions of postsynaptic cells and automated detection of synaptic puncta. We took advantage of the bright, far-red emission of FAPpost puncta for multichannel fluorescence alignment of dendrites, synapses, and presynaptic neurites to assess subtype-specific inhibitory connectivity onto L2 neocortical pyramidal (Pyr) neurons. Quantitative and compartment-specific comparisons show that PV inputs are the dominant source of inhibition at both the soma and across all dendritic branches examined and were particularly concentrated at the primary apical dendrite, a previously unrecognized compartment of L2 Pyr neurons. Our fluorescence-based synapse labeling reagents will facilitate large-scale and cell-type specific quantitation of changes in synaptic connectivity across development, learning, and disease states.

neuroscience↗