DeclMed 2023
as the organisers put it
Declarative Programming in Biology and Medicine (“DeclMed”) is a new interdisciplinary workshop that will explore declarative programming methods / paradigms and their applications in the life sciences and medicine. Given promising advances in using declarative approaches in areas such as precision medicine, bioinformatics, graph querying, modeling, and DNA computing, this workshop aims to advance the use of declarative approaches to solve complex problems in biology or medicine. The workshop will solicit abstracts, papers, tutorials, and presentations (including lightning talks). The two ...
who it's for
computational biologists, bioinformaticians, knowledge graph engineers, biomedical data scientists, programming language researchers, systems biologists
topics
functional reactive programming to chemical reaction networks; Haskell Reacto compilation; prolog-based genomic query toolkits; dynamical graph grammars for actin; Guile and Zig cross-language bindings; propagator networks for degenerate computation; signature memoization for pipelines; Biolink Model knowledge graph schema; ILP-in-the-loop neuro-symbolic constraints; aggregated graph ranking for drug repurposing
| title | author | length |
|---|---|---|
| Towards Higher-level Abstractions for Molecular Programming | Peter-Michael Osera, Titus H. Klinge, James I. Lathrop, Allison Rogers | 31m |
Proposes a concrete translation from functional reactive programming into chemical reaction networks, implemented as a Haskell library Reacto that compiles… | ||
| Strange loops: journeys in declarative logic programming in genomics and beyo... | Christopher Mungall | 54m |
Describes building a Prolog-based toolkit BitKit for genomic queries, a Make-like workflow system biom that runs on clusters, and a compact query layer… | ||
| Modeling Graph-Based Morphology of the Synaptic Spine Head | Matthew Hur, Eric Mjolsness | 23m |
Implements Dynamical Graph Grammars in a Mathematica package called Plenum to stochastically evolve actin filament graphs with rule-based propensities and… | ||
| Why code in Python+C if you can code in Lisp+Zig? | Pjotr Prins | 27m |
Argues for replacing Python+C with Guile+Zig, demonstrating a working Guile–Zig binding via the C ABI and a February proof‑of‑concept that compiles and calls… | ||
| Propagator networks for degenerate computation | Arun Isaac, Pjotr Prins | 20m |
Describes a working prototype that wires pure stateless functions into a propagator network and uses it to run degenerate computation where two implementations… | ||
| Functional Pearl: Signature Memoization for Drug Repurposing | Jeff Henrikson, John D. Osborne | 28m |
Claims that signature memoization caches subexpressions to cut edit/run/check cycles; implements a tiny embedded DSL Dagopoly in Scheme (233 lines) and Python… | ||
| Declarative Programming for Designing Neuro-Symbolic Learning Models | Parisa Kordjamshidi, Hossein Rajabi Faghihi | 27m |
DomiKnowS is a Python library that models tasks as a graph of concepts and relationships, connects arbitrary PyTorch or large language models as learners, and… | ||
| Biolink Model: a Universal Schema for Knowledge Graphs in Clinical, Biomedica... | Sierra Moxon, Deepak Unni, Michael Bada, Matt Brush, Richard Bruskiewich, Christopher Mungall, Vlado Dancik, Melissa A. Haendel, Chris Bizon, Paul Clemons | 21m |
An open‑source schema (Biolink Model) standardizes biomedical KGs by reusing ontologies (MONDO), ordering ID prefixes, and supporting class hierarchies plus… | ||
| Biomedical Data Translator - Connecting the Dots | Tyler Beck | 46m |
A cloud of connected knowledge graphs built by 14 teams answers three templated queries today and exposes an alpha release (Sept 2023) user interface that… | ||
| Addressing Treatment-Relevance in Biomedical Relation Extraction | Abdullateef I. Almudaifer, Kuleen Sasse, Kaiwen He, Michael J. Patton, Akhil Nadimpalli, Clementino Vong Do Rosario, William E. Byrd, John D. Osborne | 19m |
Fine-tuned encoder models on the BioRed corpus (NIH LitCoin) use entity-marked, modified abstracts and the CLS embedding in a multitask setup to predict four… | ||
| Aggregating combinatorial biomedical graph ranking results for drug repurposi... | Daniel Korn | 31m |
Aggregates ranked drug–disease outputs from five orthogonal graph methods into an All-Against-All dataset covering 22,506 MONDO diseases and 52,882 chemicals… | ||
| The Algorithm for Precision Medicine | Matthew Might | 53m |
Claims that data becomes the most powerful therapeutic agent and that precision medicine is best expressed declaratively. Uses the Translator/Medici Canon… | ||
| nothing matches | ||