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Results for “probabilistic modelling”

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At least 73 records · Page 4Linked to original sources
PubMed2026

LAML-Pro: joint maximum likelihood inference of cell genotypes and cell lineage trees.

MOTIVATION: Recent dynamic lineage tracing technologies use genome editing to induce heritable mutations, or edits, that accumulate across successive cell divisions. These edits are measured using single-cell sequencing or imaging, providing data to reconstruct cell lineages at single-cell resolution. Current computational approaches to infer cell lineage trees, or phylogenies, from these data perform two separate steps: (i) Identify each cell's edits (genotype) from the raw sequencing or imaging data; (ii) Infer a cell lineage tree from the cell genotypes. However, genotyping cells is an inexact process and genotype errors can yield an inaccurate lineage tree. For example, using fluorescence based-imaging to measure edits results in a high fraction (≈25%-50%) of uncertain or erroneous genotypes. RESULTS: We introduce Lineage Analysis via Maximum Likelihood with PRobabilistic Observations (LAML-Pro), an algorithm that jointly infers cell genotypes and a cell lineage tree. LAML-Pro is based on the Probabilistic Mixed-type Missing Observation (PMMO) model, which we derive to describe both the genome editing and genotype observation processes. LAML-Pro constructs lineage trees from thousands of cells in under an hour by leveraging the sparsity of transitions under the PMMO model. On simulated data, we demonstrate that LAML-Pro corrects genotype errors and infers substantially more accurate trees than existing methods which are vulnerable to genotype errors. Applied to data from two recent imaging-based lineage tracing systems, LAML-Pro reduces genotype errors by 5-fold and produces more spatially coherent lineage trees compared to existing methods. AVAILABILITY AND IMPLEMENTATION: LAML-Pro is implemented in C++ and is available as both a command-line interface and as a Python library at: github.com/raphael-group/LAML-Pro.

Cell Lineage↗
PubMed1979

Role of nuclear size in cell growth initiation.

Swiss 3T3 cells arrested in B0 (quiescent state) by reducing serum content of the medium all contain the same amount of DNA but vary in nuclear volume over approximately a twofold range. By use of flow microfluorimetry, scatterplots of nuclear volume versus DNA content were obtained in intervals after serum stimulation. The earliest cells to enter DNA synthesis were those with the largest nuclei, whereas cells with the smallest nuclei were among the latest. Regulation of cellular transit from G0 to the S phase was therefore, at least in part, deterministic, since all G0 cells did not have equal probabilities of entry into S at a given moment. All cells having the same nuclear volume did not initiate DNA synthesis at the same moment; therefore, factors other than nuclear volume must also influence this timing. Nuclear volume correlated with the maximum rate at which cells could enter S. The kinetic model of the cell cycle postulating a probabilistic event as solely responsible for entry into S thus appears too simple.

Animals↗
PubMed2026

Deconvolution of evolutionary architecture unmasks a high-risk, subclonal-rich subtype in treatment-naive small cell lung cancer.

BACKGROUND: Intratumoral heterogeneity (ITH) drives therapeutic resistance in small cell lung cancer (SCLC). However, conventional single-sample analysis has limited horizontal, cross-patient comparisons, leaving the overarching evolutionary architecture in treatment-naive tumors poorly understood. This study aims to deconvolve these architectures to identify clinically relevant evolutionary subtypes. METHODS: We analyzed whole-exome sequencing data from 41 treatment-naive SCLC patients. To overcome the cross-patient comparability bottleneck, we developed a novel probabilistic framework using a refined Gaussian Mixture Model (GMM). This standardized subclonal structures into four hierarchical strata, enabling the identification of evolutionary subtypes via unsupervised clustering. To address the scarcity of SCLC public data, prognostic concordance was robustly explored in The Cancer Genome Atlas (TCGA) lung squamous cell carcinoma (LUSC) based on shared smoking etiology, with lung adenocarcinoma (LUAD) serving as a negative control. RESULTS: The cohort robustly segregated into "Clonal-dominant" (Group 1, n=28) and "Subclonal-rich" (Group 2, n=13) subtypes. Group 1 evolution was primarily driven by tobacco signatures (SBS4). Conversely, Group 2 exhibited late-stage acquisition of a DNA mismatch repair deficiency (MMRd) signature (SBS15), fueling trace subclonal diversification. Clinically, Group 2 demonstrated a significantly lower objective response rate (ORR) to platinum-based regimens (25.0% vs. 81.3%, P=0.02). Furthermore, the Subclonal-rich architecture independently predicted inferior overall survival (OS) [adjusted hazard ratio (adj. HR) =2.93, P=0.02], driven predominantly by limited-stage disease. Cross-cancer analysis validated this histology-dependent, high-heterogeneity adverse pattern in early-stage LUSC but not in LUAD. CONCLUSIONS: This hypothesis-generating study demonstrates that a "Subclonal-rich" architecture, driven by acquired MMRd, identifies high-risk, chemo-resistant SCLC. Our GMM approach suggests that pre-existing heterogeneity may serve as a potential, histology-dependent prognostic marker that warrants prospective validation for tailoring future therapeutic regimens.

Gaussian Mixture Model (GMM)↗
PubMed2026

LAML-Pro: Joint Maximum Likelihood Inference of Cell Genotypes and Cell Lineage Trees.

MOTIVATION: Recent dynamic lineage tracing technologies use genome editing to induce heritable mutations, or edits, that accumulate across successive cell divisions. These edits are measured using single-cell sequencing or imaging, providing data to reconstruct cell lineages at single-cell resolution. Current computational approaches to infer cell lineage trees, or phylogenies, from these data perform two separate steps: (1) Identify each cell's edits (genotype) from the raw sequencing or imaging data; (2) Infer a cell lineage tree from the cell genotypes. However, genotyping cells is an inexact process and genotype errors can yield an inaccurate lineage tree. For example, using fluorescence based-imaging to measure edits results in a high fraction (≈ 25-50%) of uncertain or erroneous genotypes. RESULTS: We introduce Lineage Analysis via Maximum Likelihood with PRobabilistic Observations (LAML-Pro), an algorithm that jointly infers cell genotypes and a cell lineage tree. LAML-Pro is based on the Probabilistic Mixed-type Missing Observation (PMMO) model, which we derive to describe both the genome editing and genotype observation processes. LAML-Pro constructs lineage trees from thousands of cells in under an hour by leveraging the sparsity of transitions under the PMMO model. On simulated data, we demonstrate that LAML-Pro corrects genotype errors and infers substantially more accurate trees than existing methods which are vulnerable to genotype errors. Applied to data from two recent imaging-based lineage tracing systems, LAML-Pro reduces genotype errors by 5-fold and produces more spatially coherent lineage trees compared to existing methods. AVAILABILITY AND IMPLEMENTATION: LAML-Pro is freely available at: github.com/raphael-group/LAML-Pro.

Journal Article↗
PubMed1979

Correlation between cell size and position within the division cycle in suspension cultures of Chang liver cells.

Chang liver cells from exponentially growing suspension cultures have been separated by sedimentation at unit gravity. Determinations of the protein content per cell showed that the fractionation procedure resulted in good separation of cells of different size. On the other hand, the DNA content of individual cells from the fractions, as determined cytofluorimetrically, indicated considerable heterogeneity in the size of cells from the same stage of the division cycle. On the basis of earlier results on intermitotic growth and the variation in the length of the cell cycle in homogeneous cell populations, a mathematical model has been constructed and tested using a computer program. The present results on the size distribution of cells from the different stages of the mitotic cycle are consistent with a regeneration of size heterogeneity in each cell generation, as a result of the dispersion of intermitotic times. The variation in cell cycle times may be related to a probabilistic event in the G1 period. In the mathematical model it was necessary to include a mechanism by which the regeneration of abnormally large cells is prevented. The experimental data are compatible with a gradually increasing inhibition of growth in cells larger than a certain size (circa 400 pg protein per cell).

Animals↗
PubMedDate not supplied

[Determination of the direction and degree of an animal's tendency to migrate based on a theoretico-probabilistic analysis of its movements in a maza].

Using Markov chains a mathematical model of animal displacement in the final labyrinth is obtained. Direction and value of animal tendency towards migration from a given location point are reflected in the complex of absolute frequencies of the system appearing in its states. When estimating the tendency towards migration in the applied labyrith the whole complex of frequencies can be featured by its component, e. g. by the frequencies of animal appearance in the extreme labyrinth passages.

Animals↗
PubMed2026

Implicit and explicit statistical learning in reading: Evidence from a randomized controlled-learning study and computational modeling.

A key challenge in reading acquisition is understanding how learners extract the complex probabilistic mappings between print, meaning, and sound. Statistical learning (SL) theory offers a mechanistic account of how such mappings are acquired, whether implicitly through exposure or explicitly through instruction. We conducted a randomized controlled-learning study in Chinese, a writing system characterized by multiple sub-lexical regularities linking orthography, semantics, and phonology. Ninety-five 2nd-3rd graders with or at risk for dyslexia were randomly assigned to one of three groups: an implicit-SL training group exposed to repeated lexical and sublexical orthography-semantics-phonology associations, an explicit-SL training group receiving the same input plus explicit instruction on the sublexical print-sound mapping, and a no-SL control group. Both SL groups outperformed controls on the characters they were trained on, as well as on untrained characters that required generalization. However, only the explicit group demonstrated abstraction of print-sound mapping to novel items. Neural network simulations further revealed distinct mechanisms supporting implicit and explicit SL, consistent with a dual-system account of reading acquisition. Together, these findings (1) clarify how implicit and explicit learning distinctly support the discovery of statistical structure in written language and (2) underscore the implicit-explicit dual learning mechanism underlying reading acquisition.

Humans↗
PubMed1978

[Conformation of gamma-aminobutyric acid and its receptors].

The preferable conformations of the inhibitory transmitter gamma-aminobutyric acid (GABA) and its specific inhibitor bicuculline are due to the occupation of the GABAreceptor by a part of the bicuculline molecule that is isosteric with the biologically active conformation of GABA. In the present review are described characteristics of sodium-independence receptor sites and evaluated the regional distribution of postsynaptic receptor binding for GABA in the central nervous system. The postsynaptic GABA receptor has been labeled by direct binding of 3H-GABA. The structural analogues and antagonists of GABA were investigated for inhibition of GABA binding. The developmental changes in the activity of glutamic acid decarboxylase, the GABA uptake mechanism and GABA receptor binding in embryo brain were examined. Different models for the GABA-receptor interaction are considered. Data of the stoichiometry of GABA-receptor interactions indicate that the interaction is probabilistic and that 3 molecules of GABA are needed to activate the receptor probabilistically. It was found that 1 molecule of picrotoxin was capable of blocking the interaction with 3 GABA molecules. The hypothetical model of cooperative action of GABA-recepto-inophore complexes involving membrane mobility is also discussed. The transitive complex GABA with ligand binding of Na+, Cl- and the conformational changes of GABA-receptor is proposed.

Aminobutyrates↗
PubMed1978

Verification of the optimal probabilistic basis of aural processing in pitch of complex tones.

Periodicity pitch for complex tones has been quantitatively accounted for by a two-stage process of Fourier-frequency analysis subject to random errors and significant nonlinearities, followed by an harmonic pattern recognizer that makes an optimum probabilistic estimate of the fundamental period of musical and speech sounds. The theory predicts that periodicity pitch is a multimodal probabilistic function of a given stimulus. A clear and empirically supported distinction is made between limitations on the pitch mechanism caused by the stochastic nature of aural frequency representation and by the deterministic resolution bandwidths of aural frequency analysis. This model was developed earlier [J. L. Goldstein, J. Acoust. Soc. Am 54, 1496-1516 (1973)] to account for probabilistic data on pitch errors [A. J. M. Houtsma and J. L. Goldstein, J. Acoust. Soc. Am. 51, 520 (1972)] measured with periodic stimuli comprising two successive harmonics. This paper presents new predictions by the theory that were calculated, with computer simulation where needed, for known probabilistic pitch data from stimuli comprising three to six successive harmonics. Predicted pitch errors increase with increasing errors in estimating the frequencies of stimulus harmonics and decrease as more harmonics are added to the stimulus. Optimum processor theory fully accounts for the multicomponent pitch data on the basis of similar errors in estimating component stimulus frequencies as reported earlier, thus providing further evidence for the optimum probabilistic basis of aural signal processing in pitch of complex tones.

Auditory Cortex↗
PubMed1975

[Thoughts upon the construction of requirements of disinfection procedures concerning contaminated hands - an analysis (author's transl)].

The construction of detailed test methods for the evaluation of disinfection procedures has primarily to be based upon requirements which have to be formulated in advance. A recently proposed test model is being discussed on the basis of 5 conceivable formulations of possible requirements. Essentially, they may be allotted to two types: the one implies the comparison of the disinfection procedure to be tested as against an hypothetical procedure. The other makes use of the simple comparison with a concrete standard procedure and is preferable to the first possibility for several reasons. The presented, mathematical formulations of the structure describing the proposed model represents a first approximation in order to permit the comparison of disinfection effects on the hands under assistance of probabilistic methods and eliminating other effects inherent ot a test method.

Disinfection↗
PubMed1976

Mathematical modeling of the mastitis infection process.

Mastitis infection is a biological process with a serial structure and stochastic in nature. A mathematical model for this process was developed from Markov chain theory. The unit of the process was an individual quarter; and four infection processes for first, second, third, fourth or higher lactation were described. Two Markov matrices which probabilistically determine the transitions between seven mutually exclusive states at each stage of the process were defined. After its validation, the model was used to determine the lactational consequences of the mastitis infection by calculating expected milk-yield productivity. Expected milk-yield productivity for an individual quarter was .93, .88, .85, and .84 for first, second, third, and fourth or higher lactation. The expected milk yield productivity of a quarter as a function of its state at the beginning of the process also was calculated. The quarters infected but not clinical have the lowest productivity.

Animals↗
PubMed1978

[Behavioral tactics of schizophrenic patients and psychopathic personalities in a probabilistic setting].

In experiments on structural disturbances of prognostication in psychopathic personalities and schizophrenic patients with psychopathlike disorders on the model of "probable prognosis" the study of 2 situations was attempted: the prognosis made by the examinee of changes in the environment and the prognosis in conditions of interaction with the "opponent". The studies demonstrated the influence of different tasks on the activity and varying degree of motivation on the tactics of behaviour in probable situations. The data obtained permit to evaluate in a new light the hypotheses of disturbed probable structures of the past experience. It is concluded that at least 3 determinants should be analyzed: tasks of activity, motivation and probable characteristics of events. New facts have been obtained, concerning the disturbed prognostication in psychopathic personalities under conditions of increased significance of signals.

Antisocial Personality Disorder↗
PubMedDate not supplied

[Probabilistic reinforcement and neurotic breakdown in unrestrained dogs].

The substitution of a constant reinforcement for a random one with a probability of 0.5 in experiments on two dogs with a simple motor stereotype was attended with nervous breakdowns with motor excitation, inadequate orienting reactions or passive-defensive behaviour. The change in the probability of reinforcement from 0.5 to 0.3 had a positive effect in experiments on one dog, while in the other it developed drowsiness. In two other dogs with a complicated stereotype, the change in the mode of reinforcement was attended with a peculiar preventive effect of probabilistic, but ordered reinforcement in experimental surroundings, including signals with a probabilistic random reinforcement as well. In this case the dogs displayed primarily signs of emotional stress only. Behaviour was somewhat disturbed in one animal only when testing signals with a probabilistic random reinforcement.

Animals↗
PubMed2026

A token-pruning framework enables efficient representation of the human genome for RNA modification analysis.

MOTIVATION: Modelling long genomic sequences remains challenging due to extreme sequence length, high redundancy, and the need for biological interpretability. Although Transformer-based architectures have achieved strong performance across genomic tasks, their high computational cost and reliance on fixed tokenization strategies limit their scalability and ability to focus on biologically informative regions. RESULTS: We propose ATSFormer, a token-pruning Transformer framework for efficient and biologically informed genomic sequence modelling. ATSFormer incorporates an attention-guided and parameter-free Adaptive Token Sampling (ATS) module into Transformer layers. Guided by attention-derived importance scores, ATS dynamically retains informative tokens while probabilistically discarding redundant ones, thereby reducing sequence length, FLOPs, and memory usage without introducing additional learnable parameters or extra training procedures. Importantly, the retained tokens correspond to key contributors to model predictions, enabling ATSFormer to highlight biologically meaningful sites and sequence motifs. We evaluated ATSFormer on four benchmark RNA modification datasets derived from RMVar 2.0, covering A-to-I, m1A, m5C, and m7G. Experimental results show that ATSFormer consistently outperforms existing state-of-the-art methods while achieving substantial computational savings. Furthermore, structural analysis using AlphaFold3 supports the biological relevance of the motifs identified by ATSFormer. AVAILABILITY AND IMPLEMENTATION: The source data and code are freely available at GitHub (https://github.com/1gao2/ATSFormer) and Zenodo (https://doi.org/10.5281/zenodo.21813541).

Humans↗
PubMed2026

transfactor: transcription factor activity estimation via probabilistic gene expression deconvolution.

Gene expression is a primary modality being studied to differentiate between biological cells. Contemporary single-cell studies simultaneously measure genome-wide transcription levels for thousands of individual cells in a single experiment. While the characterization of cell population differences has often occurred through differential gene expression analysis, tiny effect sizes become statistically significant when thousands of cells are available for each population, compromising biological interpretation. Moreover, these large studies have spurred the development of methods to infer gene regulatory networks (GRNs) directly from the data, and GRN databases are becoming more comprehensive. In this work, we propose a statistical model for gene expression measures and an inference method that leverage GRNs to deconvolve transcription factor (TF) activity from gene expression, by probabilistically assigning mRNA molecules to TFs. This shifts the paradigm from investigating gene expression differences to regulatory differences at the level of TF activity, aiding interpretation and allowing prioritization of a limited number of TFs responsible for significant contributions to the observed gene expression differences. The inferred TF activities result in intuitive prioritization of TFs in terms of the (difference in) estimated number of molecules they produce, in contrast to other widely used methods relying on arbitrary enrichment scores. Our model allows the incorporation of prior information on the regulatory potential between each TF and target gene and is able to deal with both repressing and activating interactions. We compare our approach to other TF activity estimation methods using two simulation experiments and two case studies. Single-cell RNA-sequencing; TF activity; bioinformatics; GRN.

Transcription Factors↗
PubMed1976

Styles of decision-making and probability appraisal in selected obsessional and phobic patients.

A questionnaire was administered to obsessional and phobic patients and normal subjects. The results of this survey confirmed the prediction that a sizeable proportion of phobic patients report irrational expectations associated with their most feared situations. A group of phobics who reported irrational expectations, a group of obsessionals who reported an abnormal degree of checking behaviour and a group of normal subjects, took part in a probabilistic inference task. Several predictions about the differential performance of these groups were fulfilled. (i) Deviations from the optimal model for individual responses were greatest in the obsessional group. (ii) When Neuroticism was partialled out, the three groups differed with respect to amount of evidence required prior to a decision, the obsessional group having the highest score on this variable. (iii) The phobic group were more likely than the other two groups to make irrational event predictions.

Age Factors↗