AIMC Topic: Software

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NovoRank: Refinement for Peptide Sequencing Based on Spectral Clustering and Deep Learning.

Journal of proteome research
peptide sequencing is a valuable technique in mass-spectrometry-based proteomics, as it deduces peptide sequences directly from tandem mass spectra without relying on sequence databases. This database-independent method, however, relies solely on im...

DeepGOMeta for functional insights into microbial communities using deep learning-based protein function prediction.

Scientific reports
Analyzing microbial samples remains computationally challenging due to their diversity and complexity. The lack of robust de novo protein function prediction methods exacerbates the difficulty in deriving functional insights from these samples. Tradi...

Quantum-resilient software security: A fuzzy AHP-based assessment framework in the era of quantum computing.

PloS one
The introduction of quantum computing has transformed the setting of information technology, bringing both unprecedented opportunities and significant challenges. As quantum technologies continue to evolve, addressing their implications for software ...

Optimizing adult-oriented artificial intelligence for pediatric chest radiographs by adjusting operating points.

Scientific reports
The purpose of this study was to evaluate whether the optimal operating points of adult-oriented artificial intelligence (AI) software differ for pediatric chest radiographs and to assess its diagnostic performance. Chest radiographs from patients un...

Porter 6: Protein Secondary Structure Prediction by Leveraging Pre-Trained Language Models (PLMs).

International journal of molecular sciences
Accurately predicting protein secondary structure (PSSP) is crucial for understanding protein function, which is foundational to advancements in drug development, disease treatment, and biotechnology. Researchers gain critical insights into protein f...

Promises and perils of using Transformer-based models for SE research.

Neural networks : the official journal of the International Neural Network Society
Many Transformer-based pre-trained models for code have been developed and applied to code-related tasks. In this paper, we analyze 519 papers published on this topic during 2017-2023, examine the suitability of model architectures for different task...

A novel automated method for comprehensive renal cast quantification from rat kidney sections using QuPath.

American journal of physiology. Renal physiology
The presence of tubular casts within the kidney serves as an important feature when assessing the degree of renal injury. Quantification of renal tubular casts has been historically difficult due to varying cast morphologies, protein composition, and...

LevSeq: Rapid Generation of Sequence-Function Data for Directed Evolution and Machine Learning.

ACS synthetic biology
Sequence-function data provides valuable information about the protein functional landscape but is rarely obtained during directed evolution campaigns. Here, we present Long-read every variant Sequencing (LevSeq), a pipeline that combines a dual barc...

Consensus Between Radiologists, Specialists in Internal Medicine, and AI Software on Chest X-Rays in a Hospital-at-Home Service: Prospective Observational Study.

JMIR formative research
BACKGROUND: Home hospitalization is a care modality growing in popularity worldwide. Telemedicine-driven hospital-at-home (HAH) services could replace traditional hospital departments for selected patients. Chest x-rays typically serve as a key diagn...

A prospective study comparing highly qualified Molecular Tumor Boards with AI-powered software as a medical device.

International journal of clinical oncology
BACKGROUND: The implementation of cancer precision medicine in Japan is deeply intertwined with insurance reimbursement policies and requires case-by-case reviews by Molecular Tumor Boards (MTBs), which impose considerable operational burdens on heal...