17 Result(s)

Article

Scalable variable selection for two-view learning tasks with projection operators

In this paper we propose a novel variable selection method for two-view settings, or for vector-valued supervised learning problems. Our framework is able to handle extremely large scale selection tasks, where...

Sandor Szedmak, Riikka Huusari, Tat Hong Duong Le, Juho Rousu in Machine Learning (2024)

Article

Protein function prediction through multi-view multi-label latent tensor reconstruction

In last two decades, the use of high-throughput sequencing technologies has accelerated the pace of discovery of proteins. However, due to the time and resource limitations of rigorous experimental functional ...

Robert Ebo Armah-Sekum, Sandor Szedmak, Juho Rousu in BMC Bioinformatics (2024)

Article

Learning symmetry-aware atom map** in chemical reactions through deep graph matching

Accurate atom map**, which establishes correspondences between atoms in reactants and products, is a crucial step in analyzing chemical reactions. In this paper, we present a novel end-to-end approach that f...

Maryam Astero, Juho Rousu in Journal of Cheminformatics (2024)

Article

Joint structural annotation of small molecules using liquid chromatography retention order and tandem mass spectrometry data

Structural annotation of small molecules in biological samples remains a key bottleneck in untargeted metabolomics, despite rapid progress in predictive methods and tools during the past decade. Liquid chromat...

Eric Bach, Emma L. Schymanski, Juho Rousu in Nature Machine Intelligence (2022)

Article

Substrate specificity of 2-deoxy-D-ribose 5-phosphate aldolase (DERA) assessed by different protein engineering and machine learning methods

In this work, deoxyribose-5-phosphate aldolase (Ec DERA, EC 4.1.2.4) from Escherichia coli was chosen as the protein engineering target for improving the substrate preference towards smaller, non-phosphorylated a...

Sanni Voutilainen, Markus Heinonen… in Applied Microbiology and Biotechnology (2020)

Article

Leveraging multi-way interactions for systematic prediction of pre-clinical drug combination effects

We present comboFM, a machine learning framework for predicting the responses of drug combinations in pre-clinical studies, such as those based on cell lines or patient-derived cells. comboFM models the cell c...

Heli Julkunen, Anna Cichonska, Prson Gautam, Sandor Szedmak… in Nature Communications (2020)

Article

Multi-view kernel completion

In this paper, we introduce the first method that (1) can complete kernel matrices with completely missing rows and columns as opposed to individual missing kernel values, with help of information from other i...

Sahely Bhadra, Samuel Kaski, Juho Rousu in Machine Learning (2017)

Article

Critical Assessment of Small Molecule Identification 2016: automated methods

The fourth round of the Critical Assessment of Small Molecule Identification (CASMI) Contest (www.casmi-contest.org) was held in 2016, with two new cat...

Emma L. Schymanski, Christoph Ruttkies, Martin Krauss… in Journal of Cheminformatics (2017)

Article

Selected proceedings of Machine Learning in Systems Biology: MLSB 2016

Aalt D. J. van Dijk, Harri Lähdesmäki, Dick de Ridder, Juho Rousu in BMC Bioinformatics (2016)

Article

Profiling persistent tubercule bacilli from patient sputa during therapy predicts early drug efficacy

New treatment options are needed to maintain and improve therapy for tuberculosis, which caused the death of 1.5 million people in 2013 despite potential for an 86 % treatment success rate. A greater understan...

Isobella Honeyborne, Timothy D. McHugh, Iitu Kuittinen, Anna Cichonska… in BMC Medicine (2016)

Article

Multilabel classification through random graph ensembles

We present new methods for multilabel classification, relying on ensemble learning on a collection of random output graphs imposed on the multilabel, and a kernel-based structured output learner as the base cl...

Hongyu Su, Juho Rousu in Machine Learning (2015)

Article

Inferring branching pathways in genome-scale metabolic networks

A central problem in computational metabolic modelling is how to find biochemically plausible pathways between metabolites in a metabolic network. Two general, complementary frameworks have been utilized to fi...

Esa Pitkänen, Paula Jouhten, Juho Rousu in BMC Systems Biology (2009)

Article

Towards structured output prediction of enzyme function

In this paper we describe work in progress in develo** kernel methods for enzyme function prediction. Our focus is in develo** so called structured output prediction methods, where the enzymatic reaction i...

Katja Astikainen, Liisa Holm, Esa Pitkänen, Sandor Szedmak, Juho Rousu in BMC Proceedings (2008)

Article

An analytic and systematic framework for estimating metabolic flux ratios from ¹³C tracer experiments

Metabolic fluxes provide invaluable insight on the integrated response of a cell to environmental stimuli or genetic modifications. Current computational methods for estimating the metabolic fluxes from ¹³C isoto...

Ari Rantanen, Juho Rousu, Paula Jouhten, Nicola Zamboni… in BMC Bioinformatics (2008)

Article

Information Theoretic Methods for Bioinformatics

Jorma Rissanen, Peter Grünwald… in EURASIP Journal on Bioinformatics and Syst… (2008)

Article

Probabilistic modeling and machine learning in structural and systems biology

This supplement contains extended versions of a selected subset of papers presented at the workshop PMSB 2007, Probabilistic Modeling and Machine Learning in Structural and Systems Biology, Tuusula, Finland, f...

Samuel Kaski, Juho Rousu, Esko Ukkonen in BMC Bioinformatics (2007)

Article

General and Efficient Multisplitting of Numerical Attributes

Often in supervised learning numerical attributes require special treatment and do not fit the learning scheme as well as one could hope. Nevertheless, they are common in practical tasks and, therefore, need t...

Tapio Elomaa, Juho Rousu in Machine Learning (1999)