Florence d’Alché–Buc

4.7k citations

34 papers · 965 · h-index 16

Impact in

Health Informatics top 10%
Molecular Biology
- Gene Regulatory Network Analysis
- Bioinformatics and Genomic Networks
- Gene expression and cancer classification
- Microbial Metabolic Engineering and Bioproduction
- Metabolomics and Mass Spectrometry Studies

Papers in

Molecular Biology 16
- Bioinformatics and Genomic Networks 9
- Gene Regulatory Network Analysis 7
- Gene expression and cancer classification 5
- Microbial Metabolic Engineering and Bioproduction 3
- Metabolomics and Mass Spectrometry Studies 3
Artificial Intelligence 11
- Neural Networks and Applications 8

Co-authors: Liva Ralaivola (3 shared papers)Jacques Mallet (1 shared paper)Aurélien Mazurie (1 shared paper)Samuele Bottani (1 shared paper)George Michailidis (3 shared papers)Nicolas Brunel (1 shared paper)Céline Brouard (3 shared papers)Juho Rousu (2 shared papers)
Journals: Bioinformatics (6 papers)BMC Bioinformatics (3 papers)International Journal of Neural Systems (2 papers)IEEE/ACM Transactions on Audio Speech and Language Processing (1 paper)Mathematical Biosciences (1 paper)
Partner nations: France Belgium Finland

In The Last Decade

Florence d’Alché–Buc

34 papers receiving 933 citations

Peers

Replace Alioune Ngom with:

Alioune Ngom Canada

Mélanie Hilario Switzerland

Hagit Shatkay United States

Luis Rueda Canada

Thomas Schaffter United States

Shankar Vembu United States

Minghui Wang China

Genevera I. Allen United States

Xiuquan Du China

Florence d’Alché–Buc relative to Alioune Ngom Canada Alioune Ngom's profile →

Citations per field

00.5×1.5×

Alioune Ngom · 1×

×1.1 16/15

HI

×1.2 629/540

MB

×0.9 233/255

AI

×0.8 59/74

SP

×0.6 77/122

CTM

Citations per year

'16

'17

'18

'19

'20

'21

'22

'23

'24

'25

'26

Countries citing papers authored by Florence d’Alché–Buc

Since Specialization

Citations

This map shows the geographic impact of Florence d’Alché–Buc's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Florence d’Alché–Buc with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Florence d’Alché–Buc more than expected).

Fields of papers citing papers by Florence d’Alché–Buc

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Florence d’Alché–Buc. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Florence d’Alché–Buc. The network helps show where Florence d’Alché–Buc may publish in the future.

Co-authors

The 25 scholars most cited alongside Florence d’Alché–Buc, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Florence d’Alché–Buc Line = papers co-authored together Florence d’Alché–Buc links everyone, so they are left out of the graph.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Showing the 20 most-cited of 34 papers — load more, or switch the sort, to bring in the rest.

#	Work
1	Gene networks inference using dynamic Bayesian networks Bioinformatics ·Bruno-Edouard Perrin, Liva Ralaivola, Aurélien Mazurie, Samuele Bottani, Jacques Mallet, Florence d’Alché–Buc	2003	294
2	Estimating parameters and hidden variables in non-linear state-space models based on ODEs for biological networks inference Bioinformatics ·Minh Quach, Nicolas Brunel, Florence d’Alché–Buc	2007	102
3	RAR/RXR binding dynamics distinguish pluripotency from differentiation associated cis-regulatory elements Nucleic Acids Research ·Amandine Chatagnon, Philippe Veber, Valérie Morin, Justin Bedő, Gérard Triqueneaux, Marie Sémon, Vincent Laudet, Florence d’Alché–Buc, G Benoît	2015	67
4	Fast metabolite identification with Input Output Kernel Regression Bioinformatics ·Céline Brouard, Huibin Shen, Kai Dührkop, Florence d’Alché–Buc, Sebastian Böcker, Juho Rousu	2016	61
5	Autoregressive models for gene regulatory network inference: Sparsity, stability and causality issues Mathematical Biosciences ·George Michailidis, Florence d’Alché–Buc	2013	60
6	Dynamical Modeling with Kernels for Nonlinear Time Series Prediction Neural Information Processing Systems ·Liva Ralaivola, Florence d’Alché–Buc	2003	39
7	Flexible and Context-Specific AI Explainability: A Multidisciplinary Approach SSRN Electronic Journal ·Valérie Beaudouin, Isabelle Bloch, David Bounie, Stéphan Clémençon, Florence d’Alché–Buc, James Eagan, Winston Maxwell, Pavlo Mozharovskyi, Jayneel Parekh	2020	36
8	Time series filtering, smoothing and learning using the kernel kalman filter Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005. ·Liva Ralaivola, Florence d’Alché–Buc	2006	34
9	Detecting time periods of differential gene expression using Gaussian processes: an application to endothelial cells exposed to radiotherapy dose fraction Bioinformatics ·Markus Heinonen, Olivier Guipaud, Fabien Milliat, Valérie Buard, Béatrice Micheau, Georges Tarlet, Marc Benderitter, Farida Zehraoui, Florence d’Alché–Buc	2014	28
10	OKVAR-Boost: a novel boosting algorithm to infer nonlinear dynamics and interactions in gene regulatory networks Bioinformatics ·Néhémy Lim, Yasin Şenbabaoğlu, George Michailidis, Florence d’Alché–Buc	2013	24
11	Inferring biological networks with output kernel trees BMC Bioinformatics ·Pierre Geurts, Nizar Touleimat, Marie Dutreix, Florence d’Alché–Buc	2007	22
12	Evolutionary approaches for the reverse-engineering of gene regulatory networks: A study on a biologically realistic dataset BMC Bioinformatics ·Cédric Auliac, Vincent Frouin, Xavier Gidrol, Florence d’Alché–Buc	2008	20
13	TRIO LEARNING: A NEW STRATEGY FOR BUILDING HYBRID NEURAL TREES International Journal of Neural Systems ·Florence d’Alché–Buc, Didier Zwierski, Jean‐Pierre Nadal	1994	20
14	Operator-valued kernel-based vector autoregressive models for network inference Machine Learning ·Néhémy Lim, Florence d’Alché–Buc, Cédric Auliac, George Michailidis	2014	16
15	Improved Small Molecule Identification through Learning Combinations of Kernel Regression Models Metabolites ·Céline Brouard, Antoine Bassé, Florence d’Alché–Buc, Juho Rousu	2019	15
16	CycSim—an online tool for exploring and experimenting with genome-scale metabolic models Bioinformatics ·François Le Fèvre, Serge Smidtas, Cyril Combe, Maxime Durot, Florence d’Alché–Buc, Vincent Schächter	2009	15
17	Parameter estimation of perfusion models in dynamic contrast-enhanced imaging: a unified framework for model comparison Medical Image Analysis ·B Romain, Laurence Rouet, Daniel Ohayon, Olivier Lucidarme, Florence d’Alché–Buc, Véronique Letort	2016	12
18	Learning a Markov Logic network for supervised gene regulatory network inference BMC Bioinformatics ·Céline Brouard, Christel Vrain, Julie Dubois, David Castel, Marie‐Anne Debily, Florence d’Alché–Buc	2013	11
19	Wind power predictions from nowcasts to 4-hour forecasts: A learning approach with variable selection Renewable Energy ·Dimitri Bouche, Rémi Flamary, Florence d’Alché–Buc, Riwal Plougonven, Marianne Clausel, Jordi Badosa, Philippe Drobinski	2023	10
20	RULE EXTRACTION WITH FUZZY NEURAL NETWORK International Journal of Neural Systems ·Florence d’Alché–Buc, VINCENT ANDRÈS, Jean‐Pierre Nadal	1994	9

About Florence d’Alché–Buc

Florence d’Alché–Buc is a scholar working on Molecular Biology, Artificial Intelligence, Signal Processing, Radiology, Nuclear Medicine and Imaging and Biophysics, having authored 34 papers that have together received 965 indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (9 papers), Neural Networks and Applications (8 papers), Gene Regulatory Network Analysis (7 papers), Gene expression and cancer classification (5 papers), Microbial Metabolic Engineering and Bioproduction (3 papers), Metabolomics and Mass Spectrometry Studies (3 papers), MRI in cancer diagnosis (3 papers) and Radiomics and Machine Learning in Medical Imaging (3 papers). The work is most often cited by research in Health Informatics (16 citations), Molecular Biology (629 citations), Artificial Intelligence (233 citations), Signal Processing (59 citations) and Computational Theory and Mathematics (77 citations). Florence d’Alché–Buc has collaborated with scholars based in France, Belgium and Finland. Frequent co-authors include Liva Ralaivola, Jacques Mallet, Aurélien Mazurie, Samuele Bottani, George Michailidis, Nicolas Brunel, Céline Brouard, Juho Rousu, Jean‐Pierre Nadal and Huibin Shen. Their work appears in journals such as Bioinformatics, BMC Bioinformatics, International Journal of Neural Systems, IEEE/ACM Transactions on Audio Speech and Language Processing and Mathematical Biosciences.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

Explore authors with similar magnitude of impact

Florence d’Alché–Buc

Impact in

Papers in i

In The Last Decade

Florence d’Alché–Buc

Peers

Countries citing papers authored by Florence d’Alché–Buc

Fields of papers citing papers by Florence d’Alché–Buc

All Works

About Florence d’Alché–Buc

Explore authors with similar magnitude of impact

Papers in