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The increased affordability of whole genome sequencing has motivated its use for phenotypic studies. We address the problem of learning interpretable models for discrete phenotypes from whole genomes. We propose a general approach that…

Antimicrobial resistance (AMR) is a risk for patients and a burden for the healthcare system. However, AMR assays typically take several days. This study develops predictive models for AMR based on easily available clinical and…

Biological datasets amenable to applied machine learning are more available today than ever before, yet they lack adequate representation in the Data-for-Good community. Here we present a work in progress case study performing analysis on…

Machine Learning · Statistics 2016-07-06 John W. Santerre , James J. Davis , Fangfang Xia , Rick Stevens

Skin and soft tissue infections (SSTIs) are among the most frequently observed diseases in ambulatory and hospital settings. Resistance of diverse bacterial pathogens to antibiotics is a significant cause of severe SSTIs, and treatment…

Machine Learning · Computer Science 2022-03-01 Farnaz H. Foomani , Shahzad Mirza , Sahjid Mukhida , Kannuri Sriram , Zeyun Yu , Aayush Gupta , Sandeep Gopalakrishnan

Antimicrobial resistance (AMR) poses a mounting global health crisis, requiring rapid and reliable prediction frameworks that capture its complex evolutionary dynamics. Traditional antimicrobial susceptibility testing (AST), while accurate,…

Populations and Evolution · Quantitative Biology 2025-11-18 Anshul Bagaria

Antimicrobial-resistant (AMR) microbes are a growing challenge in healthcare, rendering modern medicines ineffective. AMR arises from antibiotic production and bacterial evolution, but quantifying its transmission remains difficult. With…

Machine Learning · Computer Science 2025-02-04 Qian Fu , Yuzhe Zhang , Yanfeng Shu , Ming Ding , Lina Yao , Chen Wang

Antibiotic Resistance (AR) is a critical global health challenge that necessitates the development of cost-effective, efficient, and accurate diagnostic tools. Given the genetic basis of AR, techniques such as Polymerase Chain Reaction…

Quantitative Methods · Quantitative Biology 2025-02-24 David Hagerman , Anna Johnning , Roman Naeem , Fredrik Kahl , Erik Kristiansson , Lennart Svensson

Antibiotics are a vital class of drugs closely associated with the prevention and treatment of bacterial infections. Accurate prediction of molecular antimicrobial activity remains a key challenge in the pursuit of novel antibiotic…

Quantitative Methods · Quantitative Biology 2025-09-23 R. He

Electronic health records (EHR) is an inherently multimodal register of the patient's health status characterized by static data and multivariate time series (MTS). While MTS are a valuable tool for clinical prediction, their fusion with…

The rise of Antimicrobial Resistance, particularly Multi-Drug Resistance (MDR), presents a critical challenge for clinical decision-making due to limited treatment options and delays in conventional susceptibility testing. This study…

Machine Learning · Computer Science 2026-03-03 Santanam Wishal , Riad Sahara

During times of increasing antibiotic resistance and the spread of infectious diseases like COVID-19, it is important to classify genes related to antibiotic resistance. As natural language processing has advanced with transformer-based…

Computation and Language · Computer Science 2024-01-02 Hyunwoo Yoo , Bahrad Sokhansanj , James R. Brown , Gail Rosen

Quantification of heritability is a fundamental desideratum in genetics, which allows an assessment of the contribution of additive genetic variation to the variability of a trait of interest. The traditional computational approaches for…

Applications · Statistics 2023-05-03 The Tien Mai , John A Lees , Rebecca A Gladstone , Jukka Corander

Cross-species antimicrobial resistance (AMR) prediction is fundamentally an out-of-distribution (OOD) generalization problem: models trained on one set of bacterial taxa must transfer to phylogenetically distinct genomes that may rely on…

Genomics · Quantitative Biology 2026-03-13 Huilin Tai

Whole genome sequencing (WGS) is quickly becoming the customary means for identification of antimicrobial resistance (AMR) due to its ability to obtain high resolution information about the genes and mechanisms that are causing resistance…

Genomics · Quantitative Biology 2021-07-27 Mattia Prosperi , Simone Marini , Christina Boucher , Jiang Bian

An antibiogram is a periodic summary of antibiotic resistance results of organisms from infected patients to selected antimicrobial drugs. Antibiograms help clinicians to understand regional resistance rates and select appropriate…

Machine Learning · Computer Science 2023-05-04 Xingbo Fu , Chen Chen , Yushun Dong , Anil Vullikanti , Eili Klein , Gregory Madden , Jundong Li

Antimicrobial resistance (AMR) is projected to cause up to 10 million deaths annually by 2050, underscoring the urgent need for new antibiotics. Here we present ApexAmphion, a deep-learning framework for de novo design of antibiotics that…

In this research, medical information from 1200 patients across various hospitals in Iraq was collected over a period of 3 years, from February 3, 2018, to March 5, 2021. The study encompassed several infections, including urinary tract…

Other Quantitative Biology · Quantitative Biology 2023-07-28 Maitham G. Yousif

Recently, Antimicrobial peptides (AMPs) have been an area of interest in the researches, as the first line of defense against the bacteria. They are raising attention as an efficient way of fighting multidrug resistance. Discovering and…

Quantitative Methods · Quantitative Biology 2020-05-06 Neda Zarayeneh , Zahra Hanifeloo

The worldwide increase of antimicrobial resistance (AMR) is a serious threat to human health. To avert the spread of AMR, fast reliable diagnostics tools that facilitate optimal antibiotic stewardship are an unmet need. In this regard,…

De novo therapeutic design is challenged by a vast chemical repertoire and multiple constraints, e.g., high broad-spectrum potency and low toxicity. We propose CLaSS (Controlled Latent attribute Space Sampling) - an efficient computational…

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