Results for “Inductive logic programming”

PubMed1992

Drug design by machine learning: the use of inductive logic programming to model the structure-activity relationships of trimethoprim analogues binding to dihydrofolate reductase.

The machine learning program GOLEM from the field of inductive logic programming was applied to the drug design problem of modeling structure-activity relationships. The training data for the program were 44 trimethoprim analogues and their observed inhibition of Escherichia coli dihydrofolate reductase. A further 11 compounds were used as unseen test data. GOLEM obtained rules that were statistically more accurate on the training data and also better on the test data than a Hansch linear regression model. Importantly machine learning yields understandable rules that characterized the chemistry of favored inhibitors in terms of polarity, flexibility, and hydrogen-bonding character. These rules agree with the stereochemistry of the interaction observed crystallographically.

Artificial Intelligence↗

PubMed1992

Protein secondary structure prediction using logic-based machine learning.

Many attempts have been made to solve the problem of predicting protein secondary structure from the primary sequence but the best performance results are still disappointing. In this paper, the use of a machine learning algorithm which allows relational descriptions is shown to lead to improved performance. The Inductive Logic Programming computer program, Golem, was applied to learning secondary structure prediction rules for alpha/alpha domain type proteins. The input to the program consisted of 12 non-homologous proteins (1612 residues) of known structure, together with a background knowledge describing the chemical and physical properties of the residues. Golem learned a small set of rules that predict which residues are part of the alpha-helices--based on their positional relationships and chemical and physical properties. The rules were tested on four independent non-homologous proteins (416 residues) giving an accuracy of 81% (+/- 2%). This is an improvement, on identical data, over the previously reported result of 73% by King and Sternberg (1990, J. Mol. Biol., 216, 441-457) using the machine learning program PROMIS, and of 72% using the standard Garnier-Osguthorpe-Robson method. The best previously reported result in the literature for the alpha/alpha domain type is 76%, achieved using a neural net approach. Machine learning also has the advantage over neural network and statistical methods in producing more understandable results.

Amino Acid Sequence↗

PubMed2025

Boolean matrix logic programming for active learning of gene functions in genome-scale metabolic network models.

Reasoning about hypotheses and updating knowledge through empirical observations are central to scientific discovery. In this work, we applied logic-based machine learning methods to drive biological discovery by guiding experimentation. Genome-scale metabolic network models (GEMs) - comprehensive representations of metabolic genes and reactions - are widely used to evaluate genetic engineering of biological systems. However, GEMs often fail to accurately predict the behaviour of genetically engineered cells, primarily due to incomplete annotations of gene interactions. The task of learning the intricate genetic interactions within GEMs presents computational and empirical challenges. To efficiently predict using GEM, we describe a novel approach called Boolean Matrix Logic Programming (BMLP) by leveraging Boolean matrices to evaluate large logic programs. We developed a new system, [Formula: see text], which guides cost-effective experimentation and uses interpretable logic programs to encode a state-of-the-art GEM of a model bacterial organism. Notably, [Formula: see text] successfully learned the interaction between a gene pair with fewer training examples than random experimentation, overcoming the increase in experimental design space. [Formula: see text] enables rapid optimisation of metabolic models to reliably engineer biological systems for producing useful compounds. It offers a realistic approach to creating a self-driving lab for biological discovery, which would then facilitate microbial engineering for practical applications.

Active learning↗

PubMed1977

Logic as a tool for clinical training in social work.

The paper is an attempt to illustrate the usefulness of logic as a technique in the clinical training of mental health professionals. The specific concepts that are examined include the nature of deductive and inductive reasoning, hypothesis testing, necessary and sufficient conditions, "if-then" propositions, and the nature of clinical evidence. Knowledge and use of these concepts was tested in a tutorial program directed toward students who were beginning graduate studies in the field of social work. Some of the difficulties encountered by these students, especially in the clinical aspects of their training, were directly related to an inadequate understanding of these logical forms of reasoning. It is suggested that a portion of the clinical training in mental health fields be directed towards a deeper understanding and utilization of these basic concepts.

Curriculum↗

PubMed2024

A time-resolved single-cell roadmap of the logic driving anterior neural crest diversification from neural border to migration stages.

Neural crest cells exemplify cellular diversification from a multipotent progenitor population. However, the full sequence of early molecular choices orchestrating the emergence of neural crest heterogeneity from the embryonic ectoderm remains elusive. Gene-regulatory-networks (GRN) govern early development and cell specification toward definitive neural crest. Here, we combine ultradense single-cell transcriptomes with machine-learning and large-scale transcriptomic and epigenomic experimental validation of selected trajectories, to provide the general principles and highlight specific features of the GRN underlying neural crest fate diversification from induction to early migration stages using Xenopus frog embryos as a model. During gastrulation, a transient neural border zone state precedes the choice between neural crest and placodes which includes multiple converging gene programs. During neurulation, transcription factor connectome, and bifurcation analyses demonstrate the early emergence of neural crest fates at the neural plate stage, alongside an unbiased multipotent-like lineage persisting until epithelial-mesenchymal transition stage. We also decipher circuits driving cranial and vagal neural crest formation and provide a broadly applicable high-throughput validation strategy for investigating single-cell transcriptomes in vertebrate GRNs in development, evolution, and disease.

Animals↗

PubMed2026

Repurposing anti-phage defenses to differentially arrest the viral lifecycle reveals the regulatory logic of a parasitic satellite.

Mobile genetic elements frequently encode defense mechanisms to protect their bacterial hosts from viral attack. In Vibrio cholerae, these defensive elements include phage-inducible chromosomal island-like elements (PLEs), which are phage satellites that act as highly specialized parasites of the lytic phage ICP1. While PLE transcriptional activation upon ICP1 infection is known to be temporally regulated, the underlying regulatory logic and dependencies on the progression of the phage's developmental program required for activation remain unclear. In this study, we took a novel approach to define these dependencies by introducing independent anti-phage defense systems, BREX and DarTG, as molecular roadblocks to impede the ICP1 lifecycle. We discovered that, for both ICP1 and PLE, late-stage gene expression is fundamentally uncoupled from genome replication, representing a striking departure from the standard paradigm for double-stranded DNA phages. While BREX restricts ICP1 to an immediate-early transcriptional state that stalls PLE activation, DarTG allows the phage to execute its full transcriptional cascade despite the total block in DNA replication. This permissive environment provides the necessary cues for complete PLE induction, revealing that the extent of ICP1 transcriptional progression is a key determinant of PLE transcriptional activation. Unlike other phage satellites that rely on a single cue for activation, our results demonstrate that PLE uses a progressive licensing strategy that relies on multiple cues tied to milestones in the phage's developmental program. This regulatory architecture ensures robust PLE activation resilient to phage escape.

Journal Article↗

PubMed2026

Repurposing anti-phage defenses to differentially arrest the viral lifecycle reveals the regulatory logic of a parasitic satellite.

Mobile genetic elements frequently encode defense mechanisms to protect their bacterial hosts from viral attack. In Vibrio cholerae, these defensive elements include phage-inducible chromosomal island-like elements (PLEs), which are phage satellites that act as highly specialized parasites of the lytic phage ICP1. While PLE transcriptional activation upon ICP1 infection is known to be temporally regulated, the underlying regulatory logic and dependencies on the progression of the phage's developmental program required for activation remain unclear. In this study, we took a novel approach to define these dependencies by introducing independent anti-phage defense systems, BREX and DarTG, as molecular roadblocks to impede the ICP1 lifecycle. We discovered that, for both ICP1 and PLE, late-stage gene expression is fundamentally uncoupled from genome replication, representing a striking departure from the standard paradigm for double-stranded DNA phages. While BREX restricts ICP1 to an immediate-early transcriptional state that stalls PLE activation, DarTG allows the phage to execute its full transcriptional cascade despite the total block in DNA replication. This permissive environment provides the necessary cue(s) for complete PLE induction, revealing that robust PLE activation is profoundly dependent on the transcriptional progression of its helper phage.IMPORTANCEBacteria and their viruses (phages) are locked in perpetual evolutionary conflict. Some bacteria harbor phage satellites, specialized parasites that are activated to hijack the phage's components to spread all the while inhibiting viral production. While some satellites respond to a single viral trigger, the regulation of many satellites, including clinically relevant phage-inducible chromosomal island-like elements (PLEs) in Vibrio cholerae, remains poorly understood. Here, we used bacterial defense systems as molecular roadblocks to probe how PLE activation depends on its helper phage. We found that severe disruptions to viral transcription stall PLE activation. Unexpectedly, both the virus and the satellite can execute their full transcriptional programs even when DNA replication is completely blocked, challenging a fundamental paradigm in virology. These insights reveal a sophisticated level of phage-satellite coordination, illustrating how satellite activation is tightly linked to the transcriptional state of its helper phage, a dependency that ultimately drives the dissemination of mobile genetic elements.

Vibrio cholerae↗