Sara C. Madeira

4.6k total citations · 1 hit paper
66 papers, 2.9k citations indexed

About

Sara C. Madeira is a scholar working on Molecular Biology, Artificial Intelligence and Neurology. According to data from OpenAlex, Sara C. Madeira has authored 66 papers receiving a total of 2.9k indexed citations (citations by other indexed papers that have themselves been cited), including 39 papers in Molecular Biology, 26 papers in Artificial Intelligence and 13 papers in Neurology. Recurrent topics in Sara C. Madeira's work include Gene expression and cancer classification (31 papers), Bioinformatics and Genomic Networks (25 papers) and Gene Regulatory Network Analysis (13 papers). Sara C. Madeira is often cited by papers focused on Gene expression and cancer classification (31 papers), Bioinformatics and Genomic Networks (25 papers) and Gene Regulatory Network Analysis (13 papers). Sara C. Madeira collaborates with scholars based in Portugal, Belgium and Netherlands. Sara C. Madeira's co-authors include Arlindo L. Oliveira, Rui Henriques, Joana P. Gonçalves, Alexandre P. Francisco, Isabel Sá‐Correia, Miguel C. Teixeira, Nuno P. Mira, Sandra C. dos Santos, Tânia R. Cabrito and Ana T. Freitas and has published in prestigious journals such as Nucleic Acids Research, Nature Communications and SHILAP Revista de lepidopterología.

In The Last Decade

Sara C. Madeira

65 papers receiving 2.8k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Biclustering algorithms for biological data analysis: a survey

2004 1.2k citations Sara C. Madeira, Arlindo L. Oliveira IEEE/ACM Transactions on Computational Biology and Bioinformatics profile →

Peers

Countries citing papers authored by Sara C. Madeira

Since Specialization

Citations

This map shows the geographic impact of Sara C. Madeira'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 Sara C. Madeira with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sara C. Madeira more than expected).

Fields of papers citing papers by Sara C. Madeira

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sara C. Madeira. 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 Sara C. Madeira. The network helps show where Sara C. Madeira may publish in the future.

Co-authorship network of co-authors of Sara C. Madeira

This figure shows the co-authorship network connecting the top 25 collaborators of Sara C. Madeira. A scholar is included among the top collaborators of Sara C. Madeira based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Sara C. Madeira. Sara C. Madeira is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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

20 of 20 papers shown

#	Work	Indexed citations
1	Cutting through the noise: Explaining residuals in multivariate time series with motif analysis 2025 ·Pattern Recognition ·(unknown), Sara C. Madeira, Rui Henriques	1
2	TriHSPAM: Triclustering heterogeneous longitudinal clinical data using sequential patterns 2025 ·Pattern Recognition ·Diogo F. Soares, Rui Henriques, Sara C. Madeira	1
3	Temporal stratification of amyotrophic lateral sclerosis patients using disease progression patterns 2024 ·Nature Communications ·(unknown), Diogo F. Soares, Marta Gromicho, Mamede de Carvalho, Sara C. Madeira, Pedro Tomás, Helena Aidos	6
4	Triclustering-based classification of longitudinal data for prognostic prediction: targeting relevant clinical endpoints in amyotrophic lateral sclerosis 2023 ·Scientific Reports ·Diogo F. Soares, Rui Henriques, Marta Gromicho, Mamede de Carvalho, Sara C. Madeira	7
5	Biclustering fMRI time series: a comparative study 2022 ·BMC Bioinformatics ·(unknown), Helena Aidos, Sara C. Madeira	13
6	Learning Prognostic Models Using Disease Progression Patterns: Predicting the Need for Non-Invasive Ventilation in Amyotrophic Lateral Sclerosis 2021 ·IEEE/ACM Transactions on Computational Biology and Bioinformatics ·(unknown), Marta Gromicho, Susana Pinto, Mamede de Carvalho, Sara C. Madeira	9
7	G-Tric: generating three-way synthetic datasets with triclustering solutions 2021 ·BMC Bioinformatics ·João Lobo, Rui Henriques, Sara C. Madeira	5
8	Spreading in ALS: The relative impact of upper and lower motor neuron involvement 2020 ·Annals of Clinical and Translational Neurology ·Marta Gromicho, (unknown), Hilmi Uysal, Julian Großkreutz, Magdalena Kuźma‐Kozakiewicz, Susana Pinto, Susanne Petri, Sara C. Madeira, Michael Swash, Mamede de Carvalho	38
9	Targeting the uncertainty of predictions at patient-level using an ensemble of classifiers coupled with calibration methods, Venn-ABERS, and Conformal Predictors: A case study in AD 2019 ·Journal of Biomedical Informatics ·(unknown), (unknown), Manuela Guerreiro, Alexandre de Mendonça, Sara C. Madeira	12
10	Towards a reliable prediction of conversion from Mild Cognitive Impairment to Alzheimer’s Disease: stepwise learning using time windows 2017 ·Knowledge Discovery and Data Mining ·(unknown), Alexandre de Mendonça, (unknown), Sara C. Madeira, Manuela Guerreiro	3
11	BicPAMS: software for biological data analysis with pattern-based biclustering 2017 ·BMC Bioinformatics ·Rui Henriques, (unknown), Sara C. Madeira	40
12	Predicting progression of mild cognitive impairment to dementia using neuropsychological data: a supervised learning approach using time windows 2017 ·BMC Medical Informatics and Decision Making ·(unknown), (unknown), (unknown), Dina Silva, Ana Pina Rodrigues, Isabel Santana, Alexandre de Mendonça, Manuela Guerreiro, Sara C. Madeira	34
13	BiC2PAM: constraint-guided biclustering for biological data analysis with domain knowledge 2016 ·Algorithms for Molecular Biology ·Rui Henriques, Sara C. Madeira	22
14	BicNET: Flexible module discovery in large-scale biological networks using biclustering 2016 ·Algorithms for Molecular Biology ·Rui Henriques, Sara C. Madeira	33
15	Mining coherent evolution patterns in education through biclustering. 2014 ·Educational Data Mining ·(unknown), Sara C. Madeira, Cláudia Antunes	1
16	BicPAM: Pattern-based biclustering for biomedical data analysis 2014 ·Algorithms for Molecular Biology ·Rui Henriques, Sara C. Madeira	43
17	BicSPAM: flexible biclustering using sequential patterns 2014 ·BMC Bioinformatics ·Rui Henriques, Sara C. Madeira	30
18	AliBiMotif: Integrating alignment and biclustering to unravel transcription factor binding sites in DNA sequences 2012 ·International Journal of Data Mining and Bioinformatics ·Joana P. Gonçalves, Yves Moreau, Sara C. Madeira	1
19	Identification of Regulatory Modules in Time Series Gene Expression Data Using a Linear Time Biclustering Algorithm 2009 ·IEEE/ACM Transactions on Computational Biology and Bioinformatics ·Sara C. Madeira, Miguel C. Teixeira, Isabel Sá‐Correia, Arlindo L. Oliveira	77
20	BiGGEsTS: integrated environment for biclustering analysis of time series gene expression data 2009 ·BMC Research Notes ·Joana P. Gonçalves, Sara C. Madeira, Arlindo L. Oliveira	53

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