Motivation: Due to their universal applicability, global stochastic optimization methods are popular for designing improvements of biochemical networks. The drawbacks of global stochastic optimization methods are: (i) no guarantee of finding global optima, (ii) no clear optimization run termination criteria and (iii) no criteria to detect stagnation of an optimization run. The impact of these drawbacks can be partly compensated by manual work that becomes inefficient when the solution space is large due to combinatorial explosion of adjustable parameters or for other reasons.
Results: SpaceScanner uses parallel optimization runs for automatic termination of optimization tasks in case of consensus and consecutively applies a pre-defined set of global stochastic optimization methods in case of stagnation in the currently used method. Automatic scan of adjustable parameter combination subsets for best objective function values is possible with a summary file of ranked solutions.
Availability And Implementation: https://github.com/atiselsts/spacescanner .
Contact: egils.stalidzans@lu.lv.
Supplementary Information: Supplementary data are available at Bioinformatics online.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1093/bioinformatics/btx363 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
An intelligent controlled spatiotemporal mode-locked (STML) fiber laser based on a photonic lantern (PL) is proposed and experimentally demonstrated. A pair of in-house developed PLs is spliced into the cavity in a back-to-back structure. This PL-based structure functions as a mode multiplexer/demultiplexer to generate higher-order spatial modes.
View Article and Find Full Text PDFComputer-generated holography (CGH) is an advanced technology for three-dimensional (3D) displays. While the stochastic gradient descent (SGD) method is effective for holographic optimization, its application to holographic video displays is computationally expensive, as each frame requires separate optimization. To address this, we propose a novel, to the best of our knowledge, clustering optimization strategy to accelerate the SGD process for holographic video displays.
View Article and Find Full Text PDFAttention-guided erasing for enhanced transfer learning in breast abnormality classification.
Int J Comput Assist Radiol Surg
January 2025
Pattern Recognition Lab, Friedrich-Alexander-University Erlangen-Nuremberg, Martensstr. 3, 91058, Erlangen, Bayern, Germany.
Purpose: Breast cancer remains one of the most prevalent cancers globally, necessitating effective early screening and diagnosis. This study investigates the effectiveness and generalizability of our recently proposed data augmentation technique, attention-guided erasing (AGE), across various transfer learning classification tasks for breast abnormality classification in mammography.
Methods: AGE utilizes attention head visualizations from DINO self-supervised pretraining to weakly localize regions of interest (ROI) in images.
Cost-effectiveness of targeted next-generation sequencing (tNGS) for detection of tuberculosis drug resistance in India, South Africa and Georgia: a modeling analysis.
EClinicalMedicine
January 2025
School of Epidemiology and Public Health, University of Ottawa, Ottawa, Canada.
Background: Targeted next-generation sequencing (tNGS) is promising alternative to phenotypic drug susceptibility testing (pDST) for detecting drug-resistant tuberculosis (DRTB). This study explored the potential cost-effectiveness of tNGS for the diagnosis of DR-TB across 3 settings: India, South Africa and Georgia.
Methods: To inform WHO guideline development group (GDG) on tNGS we developed a stochastic decision analysis model and assessed cost-effectiveness of tNGS for DST among rifampicin resistance individuals.
Using machine learning to predict patients with polycystic ovary disease in Chinese women.
Taiwan J Obstet Gynecol
January 2025
Graduate Institute of Applied Science and Engineering, Fu Jen Catholic University, New Taipei City, Taiwan. Electronic address:
Objective: With an estimated global frequency ranging from5 % to 21 %, polycystic ovary syndrome (PCOS) is one of the most prevalent hormonal disorders. There are many factors found to be related to PCOS. However, most of these researches used traditional methods such as multiple logistic regression (LR).
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!