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Deep generative models are able to suggest new organic molecules by generating strings, trees, and graphs representing their structure. While such models allow one to generate molecules with desirable properties, they give no guarantees…

Machine Learning · Computer Science 2019-12-05 John Bradshaw , Brooks Paige , Matt J. Kusner , Marwin H. S. Segler , José Miguel Hernández-Lobato

Since the completion of the human genome sequencing project in 2001, significant progress has been made in areas such as gene regulation editing and protein structure prediction. However, given the vast amount of genomic data, the segments…

Other Quantitative Biology · Quantitative Biology 2025-01-29 Wang Liang

As computer scientists working in bioinformatics/computational biology, we often face the challenge of coming up with an algorithm to answer a biological question. This occurs in many areas, such as variant calling, alignment, and assembly.…

Data Structures and Algorithms · Computer Science 2018-01-04 Paul Medvedev

We present a new approach for the analysis of genome-wide expression data. Our method is designed to overcome the limitations of traditional techniques, when applied to large-scale data. Rather than alloting each gene to a single cluster,…

Biological Physics · Physics 2009-11-07 Sven Bergmann , Jan Ihmels , Naama Barkai

Gene-gene and gene-environment interactions are widely believed to play significant roles in explaining the variability of complex traits. While substantial research exists in this area, a comprehensive statistical framework that addresses…

Methodology · Statistics 2026-02-18 Durba Bhattacharya , Sourabh Bhattacharya

From the response to external stimuli to cell division and death, the dynamics of living cells is based on the expression of specific genes at specific times. The decision when to express a gene is implemented by the binding and unbinding…

Molecular Networks · Quantitative Biology 2009-11-13 Johannes Berg

One aspect of evaluating the design for an experiment is the discovery of the relationships between subspaces of the data space. Initially we establish the notation and methods for evaluating an experiment with a single randomization.…

Statistics Theory · Mathematics 2009-11-23 C. J. Brien , R. A. Bailey

This document presents a combinatorial framework for analyzing assembly systems using generating functions. We explore the theory through concrete examples, such as linear polymers, and develop recursive equations to characterize valid…

Combinatorics · Mathematics 2025-01-22 Andrés Ortiz-Muñoz

Many scientific datasets are compositional in nature. Important biological examples include species abundances in ecology, cell-type compositions derived from single-cell sequencing data, and amplicon abundance data in microbiome research.…

Machine Learning · Computer Science 2024-05-29 Elisabeth Ailer , Christian L. Müller , Niki Kilbertus

Ensemble classification is an emerging approach to land cover mapping whereby the final classification output is a result of a consensus of classifiers. Intuitively, an ensemble system should consist of base classifiers which are diverse…

Machine Learning · Computer Science 2008-11-14 A. Gidudu , B. Abe , T. Marwala

Cells receive a wide variety of cellular and environmental signals, which must be processed combinatorially to generate specific and timely genetic responses. We present here a theoretical study on the combinatorial control and integration…

Soft Condensed Matter · Physics 2007-05-23 Nicolas E. Buchler , Ulrich Gerland , Terence Hwa

With the development of high throughput sequencing technology, it becomes possible to directly analyze mutation distribution in a genome-wide fashion, dissociating mutation rate measurements from the traditional underlying assumptions.…

Genomics · Quantitative Biology 2015-05-14 D. Parkhomchuk , V. S. Amstislavskiy , A. Soldatov , V. Ogryzko

In the last years, tens of thousands gene expression profiles for cells of several organisms have been monitored. Gene expression is a complex transcriptional process where mRNA molecules are translated into proteins, which control most of…

Biomolecules · Quantitative Biology 2009-11-11 T. Ochiai , J. C. Nacher , T. Akutsu

In many real world problems, features do not act alone but in combination with each other. For example, in genomics, diseases might not be caused by any single mutation but require the presence of multiple mutations. Prior work on feature…

Machine Learning · Computer Science 2023-01-12 Fergus Imrie , Alexander Norcliffe , Pietro Lio , Mihaela van der Schaar

Microbiome functions are encoded within the genes of the community-wide metagenome. A natural question is whether properties of a microbial community can be predicted just from knowing the raw DNA sequences of its members. In this work, we…

Genomics · Quantitative Biology 2026-05-13 Younhun Kim , Georg K. Gerber , Travis E. Gibson

High throughput mRNA expression profiling can be used to characterize the response of cell culture models to perturbations such as pharmacologic modulators and genetic perturbations. As profiling campaigns expand in scope, it is important…

Genomics · Quantitative Biology 2017-04-12 Tracey Filzen , Peter Kutchukian , Jeffrey Hermes , Jing Li , Matthew Tudor

Discrete mixture models provide a well-known basis for effective clustering algorithms, although technical challenges have limited their scope. In the context of gene-expression data analysis, a model is presented that mixes over a finite…

Methodology · Statistics 2012-11-12 Michael A. Newton , Lisa M. Chung

Recent experimental and theoretical approaches have attempted to quantify the physical organization (compaction and geometry) of the bacterial chromosome with its complement of proteins (the nucleoid). The genomic DNA exists in a complex…

Recent advances in bioinformatics have made high-throughput microbiome data widely available, and new statistical tools are required to maximize the information gained from these data. For example, analysis of high-dimensional microbiome…

Methodology · Statistics 2017-03-23 Neal S. Grantham , Brian J. Reich , Elizabeth T. Borer , Kevin Gross

Protein is linked to almost every life process. Therefore, analyzing the biological structure and property of protein sequences is critical to the exploration of life, as well as disease detection and drug discovery. Traditional protein…

Machine Learning · Computer Science 2021-12-08 Yijia Xiao , Jiezhong Qiu , Ziang Li , Chang-Yu Hsieh , Jie Tang