M. Reczko

发表

Lost in translation: an assessment and perspective for computational microRNA target identification

Martin Reczko, Artemis G. Hatzigeorgiou, Manolis Maragkakis, 2009, Bioinform..

Alejandra N. González-Beltrán, Ralf J. M. Weber, Rachel A. Spicer, 2017, F1000Research.

Integrated analysis of microRNA and mRNA expression and association with HIF binding reveals the complexity of microRNA expression regulation under hypoxia

Anton J. Enright, Martin Reczko, Carme Camps, 2014, Molecular Cancer.

The whole genome sequence of the Mediterranean fruit fly, Ceratitis capitata (Wiedemann), reveals insights into the biology and adaptive evolution of a highly invasive pest species

Georgios K. Georgakilas, Andrew E. Rosselot, Monica F. Poelchau, 2016, Genome Biology.

Prediction of novel microRNA genes in cancer-associated genomic regions—a combined computational and experimental approach

P. Poirazi, M. Reczko, K. Kalantidis, 2009, Nucleic acids research.

Improved MR image reconstruction from sparsely sampled scans based on neural networks

Dimitris A. Karras, Basil G. Mertzios, Dirk van Ormondt, 2001, Pattern Recognit. Lett..

The whole genome sequence of the Mediterranean fruit fly, Ceratitis capitata (Wiedemann), reveals insights into the biology and adaptive evolution of a highly invasive pest species

Georgios K. Georgakilas, Andrew E. Rosselot, Monica F. Poelchau, 2016, Genome biology.

Accurate microRNA Target Prediction Using Detailed Binding Site Accessibility and Machine Learning on Proteomics Data

Martin Reczko, Artemis G. Hatzigeorgiou, Manolis Maragkakis, 2011, Front. Gene..

Functional site prediction on the DNA sequence by artificial neural networks

Martin Reczko, Artemis G. Hatzigeorgiou, Niels Mache, 1996, Proceedings IEEE International Joint Symposia on Intelligence and Systems.

Prediction of the subcellular localization of eukaryotic proteins using sequence signals and composition

Martin Reczko, M. Reczko, Artemis Hatzigerrorgiou, 2004, Proteomics.

The future of metabolomics in ELIXIR [version 2; peer review: 3 approved]

Alejandra N. González-Beltrán, Ralf J. M. Weber, Rachel A. Spicer, 2021 .

Neuroprotection requires the functions of the RNA-binding protein HuR

M. Reczko, O. Hazapis, P. Kafasla, 2014, Cell Death and Differentiation.

Methods for Structural Inference and Functional Module Identification in Intracellular Networks

P. Poirazi, M. Reczko, M. Manioudaki, 2009 .

Association of the eNOS E298D polymorphism and the risk of myocardial infarction in the Greek population

M. Reczko, O. Landt, D. Cokkinos, 2010, BMC Medical Genetics.

Use of Mutagenesis, Genetic Mapping and Next Generation Transcriptomics to Investigate Insecticide Resistance Mechanisms

A. Hatzigeorgiou, M. Reczko, S. Oehler, 2012, PloS one.

TIER2: enhancing Trust, Integrity and Efficiency in Research through next-level Reproducibility

Haris Papageorgiou, J. Schneider, Susanna-Assunta Sansone, 2022, Research Ideas and Outcomes.

Functional microRNA targets in protein coding sequences

Ivo Grosse, Martin Reczko, Artemis G. Hatzigeorgiou, 2012, Bioinform..

Decoding the Reproductive System of the Olive Fruit Fly, Bactrocera oleae

M. Reczko, M. Gregoriou, K. Tsoumani, 2018, bioRxiv.

Methods for Dynamical Inference in Intracellular Networks

M. Reczko, E. Tzamali, Panayiota Poirazi, 2009 .

DIANA-microT web server v5.0: service integration into miRNA functional analysis workflows

Martin Reczko, Artemis G. Hatzigeorgiou, Thanasis Vergoulis, 2013, Nucleic Acids Res..

MicroRNAs and Cancer—The Search Begins!

Martin Reczko, Panayiota Poirazi, Anastasis Oulas, 2009, IEEE Transactions on Information Technology in Biomedicine.

Discrete Clusters of Virus-Encoded MicroRNAs Are Associated with Complementary Strands of the Genome and the 7.2-Kilobase Stable Intron in Murine Cytomegalovirus

Martin Reczko, Peter Ghazal, Javier Santoyo-Lopez, 2007, Journal of Virology.

Support Vector Machines for Predicting microRNA Hairpins

Molly Megraw, Martin Reczko, Artemis G. Hatzigeorgiou, 2006, BIOCOMP.

DIANA-LncBase: experimentally verified and computationally predicted microRNA targets on long non-coding RNAs

Martin Reczko, Artemis G. Hatzigeorgiou, Theodore Dalamagas, 2012, Nucleic Acids Res..

Divergent Innate and Epithelial Functions of the RNA-Binding Protein HuR in Intestinal Inflammation

M. Reczko, D. Kontoyiannis, I. Karakasiliotis, 2018, Front. Immunol..

TarBase 6.0: capturing the exponential growth of miRNA targets with experimental support

Nectarios Koziris, Martin Reczko, Artemis G. Hatzigeorgiou, 2011, Nucleic Acids Res..

Accurate microRNA target prediction correlates with protein repression levels

Nectarios Koziris, Timos K. Sellis, Panayiotis Tsanakas, 2009, BMC Bioinformatics.

RNA Sequencing Reveals that Kaposi Sarcoma-Associated Herpesvirus Infection Mimics Hypoxia Gene Expression Signature

J. Ragoussis, M. Reczko, F. Pezzella, 2017, PLoS pathogens.

Next-Generation Sequencing Analysis Reveals Differential Expression Profiles of MiRNA-mRNA Target Pairs in KSHV-Infected Cells

J. Ragoussis, M. Reczko, F. Pezzella, 2015, PloS one.

A computational exploration of bacterial metabolic diversity identifying metabolic interactions and growth-efficient strain communities

Ioannis G. Tollis, Martin Reczko, Eleftheria Tzamali, 2011, BMC Systems Biology.

DIANA-microT web server: elucidating microRNA functions through target prediction

Nectarios Koziris, Timos K. Sellis, Panayiotis Tsanakas, 2009, Nucleic Acids Res..

DIANA-microT Web server upgrade supports Fly and Worm miRNA target prediction and bibliographic miRNA to disease association

Nectarios Koziris, Martin Reczko, Artemis G. Hatzigeorgiou, 2011, Nucleic Acids Res..

DIANA-mirPath: Integrating human and mouse microRNAs in pathways

Martin Reczko, Artemis G. Hatzigeorgiou, Manolis Maragkakis, 2009, Bioinform..

The database of experimentally supported targets: a functional update of TarBase

Martin Reczko, Artemis G. Hatzigeorgiou, Giorgos L. Papadopoulos, 2008, Nucleic Acids Res..

A Positive Regulatory Loo p between a Wnt-Regulated Non-coding RNA and ASCL 2 Controls Intestinal Stem Cell Fate Graphical

A. Hatzigeorgiou, M. Reczko, P. Moulos, 2016 .

Applications of Artificial Neural Networks in Genome Research

M. Reczko, S. Suhai, M. Reczko, 1994 .

DIANA miRPath v.2.0: investigating the combinatorial effect of microRNAs in pathways

Martin Reczko, Artemis G. Hatzigeorgiou, Thanasis Vergoulis, 2012, Nucleic Acids Res..

Identification of microRNA-221/222 and microRNA-323-3p association with rheumatoid arthritis via predictions using the human tumour necrosis factor transgenic mouse model

J. Ragoussis, A. Hatzigeorgiou, G. Kollias, 2012, Annals of the rheumatic diseases.

The DEF data base of sequence based protein fold class predictions.

H. Bohr, M. Reczko, M Reczko, 1994, Nucleic acids research.

Bidirectional Long Short-Term Memory Networks for Predicting the Subcellular Localization of Eukaryotic Proteins

T. Thireou, M. Reczko, M. Reczko, 2007, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

The Effect of Smoke Combined with the Multicancer Marker, Rs6983267,Located at Region 3 of Chromosome 8q24 in Prostate Cancer Patients

M. Reczko, O. Landt, K. Ntoumas, 2012 .

A Positive Regulatory Loop between a Wnt-Regulated Non-coding RNA and ASCL2 Controls Intestinal Stem Cell Fate.

A. Hatzigeorgiou, M. Reczko, P. Moulos, 2016, Cell reports.

Olive fly transcriptomics analysis implicates energy metabolism genes in spinosad resistance

J. Ragoussis, M. Reczko, F. Zalom, 2014, BMC Genomics.

Finding Signal Peptides in Human Protein Sequences Using Recurrent Neural Networks

Martin Reczko, Artemis G. Hatzigeorgiou, Petko Fiziev, 2002, WABI.

Protein secondary structure prediction with partially recurrent neural networks.

M Reczko, M. Reczko, 1993, SAR and QSAR in environmental research.

Multistate Time-Delay Neural Networks for the recognition of POL II promoter sequences

Martin Reczko, Niels Mache, M. Reczko, 1996 .

The molecular biology of the olive fly comes of age

J. Ragoussis, M. Reczko, K. Tsoumani, 2014, BMC Genetics.

Encoding of Spatio-Temporal Input Characteristics by a CA1 Pyramidal Neuron Model

Martin Reczko, Panayiota Poirazi, Eleftheria Kyriaki Pissadaki, 2010, PLoS Comput. Biol..

Bee foraging preferences, microbiota and pathogens revealed by direct shotgun metagenomics of honey

M. Reczko, P. Hatzis, S. Patalano, 2021, bioRxiv.

The future of metabolomics in ELIXIR.

Alejandra N. González-Beltrán, Ralf J. M. Weber, Rachel A. Spicer, 2017, F1000Research.

The future of metabolomics in ELIXIR

Alejandra N. González-Beltrán, Ralf J. M. Weber, Rachel A. Spicer, 2017, F1000Research.

DeepFoldit - A Deep Reinforcement Learning Neural Network Folding Proteins pdf

Martin Reczko, Dimitra N. Panou, M. Reczko, 2020, ArXiv.

The future of metabolomics in ELIXIR [version 1; peer review: 2 approved, 1 approved with reservations]

Alejandra N. González-Beltrán, Ralf J. M. Weber, Rachel A. Spicer, 2021 .

Using Treemaps to Visualize Phylogenetic Trees

Ioannis G. Tollis, Alexandros Stamatakis, Martin Reczko, 2005, ISBMDA.

Detection of Eukaryotic POL II Promoters with Multi-State Time-Delay Neural Networks

Martin Reczko, Artemis G. Hatzigeorgiou, Paul Levi, 1996, German Conference on Bioinformatics.

Polymorphisms of the NRAMP1 gene: Distribution and susceptibility to the development of pulmonary tuberculosis in the Greek population

M. Reczko, N. Drakoulis, D. Orphanidou, 2011, Medical science monitor : international medical journal of experimental and clinical research.

Visualization of Functional Aspects of microRNA Regulatory Networks Using the Gene Ontology

Ioannis G. Tollis, Martin Reczko, Alkiviadis Symeonidis, 2006, ISBMDA.

ELECTROLBERT: Combining Replaced Token Detection and Sentence Order Prediction

M. Reczko, 2022, Conference and Labs of the Evaluation Forum.

The benefit of cooperation: Identifying growth-efficient interacting strains of Escherichia coli using metabolic flux balance models

Martin Reczko, Eleftheria Tzamali, M. Reczko, 2008, 2008 8th IEEE International Conference on BioInformatics and BioEngineering.

DIANA-EST: a statistical analysis

Martin Reczko, Artemis G. Hatzigeorgiou, Petko Fiziev, 2001, Bioinform..

Bacterial production and direct functional screening of expanded molecular libraries for discovering inhibitors of protein aggregation

C. Dobson, M. Reczko, M. Vendruscolo, 2019, Science Advances.

The future of metabolomics in ELIXIR

Alejandra N. González-Beltrán, Ralf J. M. Weber, Rachel A. Spicer, 2017 .

The future of metabolomics in ELIXIR

Alejandra N. González-Beltrán, Ralf J. M. Weber, Rachel A. Spicer, 2017, F1000Research.

SCHeMa: Scheduling Scientific Containers on a Cluster of Heterogeneous Machines

M. Reczko, Thanasis Vergoulis, Theodore Dalamagas, 2021, SSDBM.

Identifying novel regulatory effects for clinically relevant genes through the study of the Greek population

J. Ragoussis, A. Dimas, M. Reczko, 2023, BMC Genomics.

Protein Fold Class Prediction: New Methods of Statistical Classification

Martin Reczko, Sándor Suhai, Janet Grassmann, 1999, ISMB.

Functional microRNA targets in protein coding sequences

A. Hatzigeorgiou, I. Grosse, P. Alexiou, 2012, Bioinform..

Identification of microRNA-221/222 and microRNA-323-3p association with rheumatoid arthritis via predictions using the human tumour necrosis factor transgenic mouse model

J. Ragoussis, A. Hatzigeorgiou, G. Kollias, 2012, Annals of the rheumatic diseases.