Format
Sort by
Items per page

Send to

Choose Destination

Search results

Items: 1 to 50 of 76

1.

Machine Learning Polymer Models of Three-Dimensional Chromatin Organization in Human Lymphoblastoid Cells.

Al Bkhetan Z, Kadlof M, Kraft A, Plewczynski D.

Methods. 2019 Mar 7. pii: S1046-2023(18)30334-7. doi: 10.1016/j.ymeth.2019.03.002. [Epub ahead of print]

PMID:
30853548
2.

Intermingling of chromosome territories.

Szczepińska T, Rusek AM, Plewczynski D.

Genes Chromosomes Cancer. 2019 Jan 21. doi: 10.1002/gcc.22736. [Epub ahead of print] Review.

PMID:
30828902
3.

Dendritic Spines Taxonomy: The Functional and Structural Classification • Time-Dependent Probabilistic Model of Neuronal Activation.

Urban P, Rezaei V, Bokota G, Denkiewicz M, Basu S, Plewczyński D.

J Comput Biol. 2019 Feb 27. doi: 10.1089/cmb.2018.0155. [Epub ahead of print]

PMID:
30810368
4.

Disentangling the complexity of low complexity proteins.

Mier P, Paladin L, Tamana S, Petrosian S, Hajdu-Soltész B, Urbanek A, Gruca A, Plewczynski D, Grynberg M, Bernadó P, Gáspári Z, Ouzounis CA, Promponas VJ, Kajava AV, Hancock JM, Tosatto SCE, Dosztanyi Z, Andrade-Navarro MA.

Brief Bioinform. 2019 Jan 30. doi: 10.1093/bib/bbz007. [Epub ahead of print]

PMID:
30698641
5.

Upregulation of MLK4 promotes migratory and invasive potential of breast cancer cells.

Marusiak AA, Prelowska MK, Mehlich D, Lazniewski M, Kaminska K, Gorczynski A, Korwat A, Sokolowska O, Kedzierska H, Golab J, Biernat W, Plewczynski D, Brognard J, Nowis D.

Oncogene. 2018 Dec 14. doi: 10.1038/s41388-018-0618-0. [Epub ahead of print]

PMID:
30552384
6.

ShapeGTB: the role of local DNA shape in prioritization of functional variants in human promoters with machine learning.

Malkowska M, Zubek J, Plewczynski D, Wyrwicz LS.

PeerJ. 2018 Nov 29;6:e5742. doi: 10.7717/peerj.5742. eCollection 2018.

7.

Emerging and threatening infectious diseases.

Basu S, Plewczynski D.

Brief Funct Genomics. 2018 Nov 26;17(6):372-373. doi: 10.1093/bfgp/ely038. No abstract available.

PMID:
30476067
8.

Author Correction: Quantitative 3-D morphometric analysis of individual dendritic spines.

Basu S, Saha PK, Roszkowska M, Magnowska M, Baczynska E, Das N, Plewczynski D, Wlodarczyk J.

Sci Rep. 2018 Nov 15;8(1):17142. doi: 10.1038/s41598-018-35164-2.

9.

Oncogenes expand during evolution to withstand somatic amplification.

Wang X, Li X, Zhang L, Wong SH, Wang MHT, Tse G, Dai RZW, Nakatsu G, Coker OO, Chen Z, Ko H, Chan JYK, Liu T, Cheng CHK, Cheng ASL, To KF, Plewczynski D, Sung JJY, Yu J, Gin T, Chan MTV, Wu WKK.

Ann Oncol. 2018 Nov 1;29(11):2254-2260. doi: 10.1093/annonc/mdy397.

PMID:
30204835
10.

One protein to rule them all: The role of CCCTC-binding factor in shaping human genome in health and disease.

Lazniewski M, Dawson WK, Rusek AM, Plewczynski D.

Semin Cell Dev Biol. 2018 Oct 11. pii: S1084-9521(17)30591-8. doi: 10.1016/j.semcdb.2018.08.003. [Epub ahead of print] Review.

PMID:
30096365
11.

Inhibition of protein disulfide isomerase induces differentiation of acute myeloid leukemia cells.

Chlebowska-Tuz J, Sokolowska O, Gaj P, Lazniewski M, Firczuk M, Borowiec K, Sas-Nowosielska H, Bajor M, Malinowska A, Muchowicz A, Ramji K, Stawinski P, Sobczak M, Pilch Z, Rodziewicz-Lurzynska A, Zajac M, Giannopoulos K, Juszczynski P, Basak GW, Plewczynski D, Ploski R, Golab J, Nowis D.

Haematologica. 2018 Nov;103(11):1843-1852. doi: 10.3324/haematol.2018.190231. Epub 2018 Jul 12.

12.

3gClust: Human Protein Cluster Analysis.

Halder AK, Chatterjee P, Nasipuri M, Plewczynski D, Basu S.

IEEE/ACM Trans Comput Biol Bioinform. 2018 May 30. doi: 10.1109/TCBB.2018.2840996. [Epub ahead of print]

PMID:
29993556
13.

Three-dimensional Epigenome Statistical Model: Genome-wide Chromatin Looping Prediction.

Al Bkhetan Z, Plewczynski D.

Sci Rep. 2018 Mar 26;8(1):5217. doi: 10.1038/s41598-018-23276-8.

14.

Three-dimensional organization and dynamics of the genome.

Szalaj P, Plewczynski D.

Cell Biol Toxicol. 2018 Oct;34(5):381-404. doi: 10.1007/s10565-018-9428-y. Epub 2018 Mar 22. Review.

15.

Quantitative 3-D morphometric analysis of individual dendritic spines.

Basu S, Saha PK, Roszkowska M, Magnowska M, Baczynska E, Das N, Plewczynski D, Wlodarczyk J.

Sci Rep. 2018 Feb 23;8(1):3545. doi: 10.1038/s41598-018-21753-8. Erratum in: Sci Rep. 2018 Nov 15;8(1):17142.

16.

Clinical and molecular characteristics of newly reported mitochondrial disease entity caused by biallelic PARS2 mutations.

Ciara E, Rokicki D, Lazniewski M, Mierzewska H, Jurkiewicz E, Bekiesińska-Figatowska M, Piekutowska-Abramczuk D, Iwanicka-Pronicka K, Szymańska E, Stawiński P, Kosińska J, Pollak A, Pronicki M, Plewczyński D, Płoski R, Pronicka E.

J Hum Genet. 2018 Apr;63(4):473-485. doi: 10.1038/s10038-017-0401-z. Epub 2018 Feb 6.

PMID:
29410512
17.

The structural variability of the influenza A hemagglutinin receptor-binding site.

Lazniewski M, Dawson WK, Szczepinska T, Plewczynski D.

Brief Funct Genomics. 2018 Nov 26;17(6):415-427. doi: 10.1093/bfgp/elx042.

18.

RNA structure interactions and ribonucleoprotein processes of the influenza A virus.

Dawson WK, Lazniewski M, Plewczynski D.

Brief Funct Genomics. 2018 Nov 26;17(6):402-414. doi: 10.1093/bfgp/elx028.

19.

Social adaptation in multi-agent model of linguistic categorization is affected by network information flow.

Zubek J, Denkiewicz M, Barański J, Wróblewski P, Rączaszek-Leonardi J, Plewczynski D.

PLoS One. 2017 Aug 15;12(8):e0182490. doi: 10.1371/journal.pone.0182490. eCollection 2017.

20.

Novel neuro-audiological findings and further evidence for TWNK involvement in Perrault syndrome.

Ołdak M, Oziębło D, Pollak A, Stępniak I, Lazniewski M, Lechowicz U, Kochanek K, Furmanek M, Tacikowska G, Plewczynski D, Wolak T, Płoski R, Skarżyński H.

J Transl Med. 2017 Feb 8;15(1):25. doi: 10.1186/s12967-017-1129-4.

21.

Computational Approach to Dendritic Spine Taxonomy and Shape Transition Analysis.

Bokota G, Magnowska M, Kuśmierczyk T, Łukasik M, Roszkowska M, Plewczynski D.

Front Comput Neurosci. 2016 Dec 23;10:140. doi: 10.3389/fncom.2016.00140. eCollection 2016.

22.

An integrated 3-Dimensional Genome Modeling Engine for data-driven simulation of spatial genome organization.

Szałaj P, Tang Z, Michalski P, Pietal MJ, Luo OJ, Sadowski M, Li X, Radew K, Ruan Y, Plewczynski D.

Genome Res. 2016 Dec;26(12):1697-1709. Epub 2016 Oct 27.

23.

Predicting Post-Translational Modifications from Local Sequence Fragments Using Machine Learning Algorithms: Overview and Best Practices.

Tatjewski M, Kierczak M, Plewczynski D.

Methods Mol Biol. 2017;1484:275-300. doi: 10.1007/978-1-4939-6406-2_19.

PMID:
27787833
24.

3DFlu: database of sequence and structural variability of the influenza hemagglutinin at population scale.

Mazzocco G, Lazniewski M, Migdał P, Szczepińska T, Radomski JP, Plewczynski D.

Database (Oxford). 2016 Oct 2;2016. pii: baw130. Print 2016.

25.

3D-GNOME: an integrated web service for structural modeling of the 3D genome.

Szalaj P, Michalski PJ, Wróblewski P, Tang Z, Kadlof M, Mazzocco G, Ruan Y, Plewczynski D.

Nucleic Acids Res. 2016 Jul 8;44(W1):W288-93. doi: 10.1093/nar/gkw437. Epub 2016 May 16.

26.

2dSpAn: semiautomated 2-d segmentation, classification and analysis of hippocampal dendritic spine plasticity.

Basu S, Plewczynski D, Saha S, Roszkowska M, Magnowska M, Baczynska E, Wlodarczyk J.

Bioinformatics. 2016 Aug 15;32(16):2490-8. doi: 10.1093/bioinformatics/btw172. Epub 2016 Apr 1.

PMID:
27153678
27.

Computational inference of H3K4me3 and H3K27ac domain length.

Zubek J, Stitzel ML, Ucar D, Plewczynski DM.

PeerJ. 2016 Mar 14;4:e1750. doi: 10.7717/peerj.1750. eCollection 2016.

28.

PDP-CON: prediction of domain/linker residues in protein sequences using a consensus approach.

Chatterjee P, Basu S, Zubek J, Kundu M, Nasipuri M, Plewczynski D.

J Mol Model. 2016 Apr;22(4):72. doi: 10.1007/s00894-016-2933-0. Epub 2016 Mar 11.

29.

Detecting reliable non interacting proteins (NIPs) significantly enhancing the computational prediction of protein-protein interactions using machine learning methods.

Srivastava A, Mazzocco G, Kel A, Wyrwicz LS, Plewczynski D.

Mol Biosyst. 2016 Mar;12(3):778-85. doi: 10.1039/c5mb00672d.

PMID:
26738778
30.

CTCF-Mediated Human 3D Genome Architecture Reveals Chromatin Topology for Transcription.

Tang Z, Luo OJ, Li X, Zheng M, Zhu JJ, Szalaj P, Trzaskoma P, Magalska A, Wlodarczyk J, Ruszczycki B, Michalski P, Piecuch E, Wang P, Wang D, Tian SZ, Penrad-Mobayed M, Sachs LM, Ruan X, Wei CL, Liu ET, Wilczynski GM, Plewczynski D, Li G, Ruan Y.

Cell. 2015 Dec 17;163(7):1611-27. doi: 10.1016/j.cell.2015.11.024. Epub 2015 Dec 10.

31.

The proline-rich region of glyceraldehyde-3-phosphate dehydrogenase from human sperm may bind SH3 domains, as revealed by a bioinformatic study of low-complexity protein segments.

Tatjewski M, Gruca A, Plewczynski D, Grynberg M.

Mol Reprod Dev. 2016 Feb;83(2):144-8. doi: 10.1002/mrd.22606. Epub 2016 Jan 17.

PMID:
26660717
32.

A combined systems and structural modeling approach repositions antibiotics for Mycoplasma genitalium.

Kazakiewicz D, Karr JR, Langner KM, Plewczynski D.

Comput Biol Chem. 2015 Dec;59 Pt B:91-7. doi: 10.1016/j.compbiolchem.2015.07.007. Epub 2015 Jul 30.

PMID:
26271684
33.

Multi-level machine learning prediction of protein-protein interactions in Saccharomyces cerevisiae.

Zubek J, Tatjewski M, Boniecki A, Mnich M, Basu S, Plewczynski D.

PeerJ. 2015 Jul 2;3:e1041. doi: 10.7717/peerj.1041. eCollection 2015.

34.

Binding Activity Prediction of Cyclin-Dependent Inhibitors.

Saha I, Rak B, Bhowmick SS, Maulik U, Bhattacharjee D, Koch U, Lazniewski M, Plewczynski D.

J Chem Inf Model. 2015 Jul 27;55(7):1469-82. doi: 10.1021/ci500633c. Epub 2015 Jul 10.

PMID:
26079845
35.

Application of machine learning method in genomics and proteomics.

Lin H, Chen W, Anandakrishnan R, Plewczynski D.

ScientificWorldJournal. 2015;2015:914780. doi: 10.1155/2015/914780. Epub 2015 Apr 19. No abstract available.

36.

Role of the host genetic variability in the influenza A virus susceptibility.

Arcanjo AC, Mazzocco G, de Oliveira SF, Plewczynski D, Radomski JP.

Acta Biochim Pol. 2014;61(3):403-19. Epub 2014 Sep 4. Review.

37.

Ensemble learning prediction of protein-protein interactions using proteins functional annotations.

Saha I, Zubek J, Klingström T, Forsberg S, Wikander J, Kierczak M, Maulik U, Plewczynski D.

Mol Biosyst. 2014 Apr;10(4):820-30. doi: 10.1039/c3mb70486f. Epub 2014 Jan 27.

PMID:
24469380
38.

PPIcons: identification of protein-protein interaction sites in selected organisms.

Sriwastava BK, Basu S, Maulik U, Plewczynski D.

J Mol Model. 2013 Sep;19(9):4059-70. doi: 10.1007/s00894-013-1886-9. Epub 2013 Jun 2.

39.

Consensus classification of human leukocyte antigen class II proteins.

Saha I, Mazzocco G, Plewczynski D.

Immunogenetics. 2013 Feb;65(2):97-105. doi: 10.1007/s00251-012-0665-6. Epub 2012 Nov 16. Erratum in: Immunogenetics. 2013 Apr;65(4):313.

40.

AMS 4.0: consensus prediction of post-translational modifications in protein sequences.

Plewczynski D, Basu S, Saha I.

Amino Acids. 2012 Aug;43(2):573-82. doi: 10.1007/s00726-012-1290-2. Epub 2012 May 4.

41.

Improved differential evolution for microarray analysis.

Saha I, Plewczynski D, Maulik U, Bandyopadhyay S.

Int J Data Min Bioinform. 2012;6(1):86-103.

PMID:
22479820
42.

Fuzzy clustering of physicochemical and biochemical properties of amino acids.

Saha I, Maulik U, Bandyopadhyay S, Plewczynski D.

Amino Acids. 2012 Aug;43(2):583-94. doi: 10.1007/s00726-011-1106-9. Epub 2011 Oct 13.

43.

PSP_MCSVM: brainstorming consensus prediction of protein secondary structures using two-stage multiclass support vector machines.

Chatterjee P, Basu S, Kundu M, Nasipuri M, Plewczynski D.

J Mol Model. 2011 Sep;17(9):2191-201. doi: 10.1007/s00894-011-1102-8. Epub 2011 May 19.

44.

PPI_SVM: prediction of protein-protein interactions using machine learning, domain-domain affinities and frequency tables.

Chatterjee P, Basu S, Kundu M, Nasipuri M, Plewczynski D.

Cell Mol Biol Lett. 2011 Jun;16(2):264-78. doi: 10.2478/s11658-011-0008-x. Epub 2011 Mar 20.

45.

GIDMP: good protein-protein interaction data metamining practice.

Plewczynski D, Klingström T.

Cell Mol Biol Lett. 2011 Jun;16(2):258-63. doi: 10.2478/s11658-011-0004-1. Epub 2011 Mar 9.

46.

Detailed mechanism of squalene epoxidase inhibition by terbinafine.

Nowosielski M, Hoffmann M, Wyrwicz LS, Stepniak P, Plewczynski DM, Lazniewski M, Ginalski K, Rychlewski L.

J Chem Inf Model. 2011 Feb 28;51(2):455-62. doi: 10.1021/ci100403b. Epub 2011 Jan 13.

PMID:
21229992
47.

HarmonyDOCK: the structural analysis of poses in protein-ligand docking.

Plewczynski D, Philips A, Von Grotthuss M, Rychlewski L, Ginalski K.

J Comput Biol. 2014 Mar;21(3):247-56. doi: 10.1089/cmb.2009.0111. Epub 2010 Nov 20.

PMID:
21091053
48.

Brainstorming: weighted voting prediction of inhibitors for protein targets.

Plewczynski D.

J Mol Model. 2011 Sep;17(9):2133-41. doi: 10.1007/s00894-010-0854-x. Epub 2010 Sep 21.

49.

Protein-protein interaction and pathway databases, a graphical review.

Klingström T, Plewczynski D.

Brief Bioinform. 2011 Nov;12(6):702-13. doi: 10.1093/bib/bbq064. Epub 2010 Sep 17.

PMID:
20851835
50.

VoteDock: consensus docking method for prediction of protein-ligand interactions.

Plewczynski D, Łaźniewski M, von Grotthuss M, Rychlewski L, Ginalski K.

J Comput Chem. 2011 Mar;32(4):568-81. doi: 10.1002/jcc.21642. Epub 2010 Sep 1.

Supplemental Content

Loading ...
Support Center