Citations Report - Advanced Techniques in Biology and Medicine

Advanced Techniques in Biology & Medicine : Citations & Metrics Report

Articles published in Advanced Techniques in Biology & Medicine have been cited by esteemed scholars and scientists all around the world. Advanced Techniques in Biology & Medicine has got h-index 14, which means every article in Advanced Techniques in Biology & Medicine has got 14 average citations.

Following are the list of articles that have cited the articles published in Advanced Techniques in Biology & Medicine.

	2021	2020	2019	2018	2017	2016
Year wise published articles	60	42	6	13	53	41
Year wise citations received	140	106	105	127	116	101

Journal total citations count	1015
Journal impact factor	2.30
Journal 5 years impact factor	3.43
Journal cite score	4.03
Journal h-index	14
Journal h-index since 2018	11

Important citations (825)

morotomi t, washio a, kitamura c. current and future options for dental pulp therapy. japanese dental science review. 2019 nov 1;55(1):5-11. View at Publisher View at Google Scholar
badaczewska-dawid a. modelowanie struktury i dynamiki biaÅ‚ek z uÅ¼yciem modeli gruboziarnistych o róÅ¼nej skali rozdzielczoÅ›ci. View at Publisher View at Google Scholar
rodríguez-guerra pedregal j. development and application of a computational platform for complex molecular design. View at Publisher View at Google Scholar
hattori lt, benitez cm, gutoski m, aquino nm, lopes hs. a novel approach to protein folding prediction based on long short-term memory networks: a preliminary investigation and analysis. in2018 international joint conference on neural networks (ijcnn) 2018 jul 8 (pp. 1-8). ieee. View at Publisher View at Google Scholar
jia l, gao h. machine learning in drug discovery and development. View at Publisher View at Google Scholar
estrada t, benson j, carrillo-cabada h, razavi am, cuendet ma, weinstein h, deelman e, taufer m. graphic encoding of macromolecules for efficient high-throughput analysis. inproceedings of the 2018 acm international conference on bioinformatics, computational biology, and health informatics 2018 aug 15 (pp. 315-324). acm. View at Publisher View at Google Scholar
rajesh t. review on heart sound wavelet neural network applications. View at Publisher View at Google Scholar
khalatbari l, kangavari mr, hosseini s, yin h, cheung nm. mcp: a multi-component learning machine to predict protein secondary structure. computers in biology and medicine. 2019 jul 1;110:144-55. View at Publisher View at Google Scholar
cárdenas domínguez mi. a computational intelligence analysis of g proteincoupled receptor sequinces for pharmacoproteomic applications. View at Publisher View at Google Scholar
hanson j, paliwal kk, litfin t, yang y, zhou y. getting to know your neighbor: protein structure prediction comes of age with contextual machine learning. journal of computational biology. 2019 aug 30. View at Publisher View at Google Scholar
hasic h, buza e, akagic a. a hybrid method for prediction of protein secondary structure based on multiple artificial neural networks. in2017 40th international convention on information and communication technology, electronics and microelectronics (mipro) 2017 may 22 (pp. 1195-1200). ieee. View at Publisher View at Google Scholar
telenti a, lippert c, chang pc, depristo m. deep learning of genomic variation and regulatory network data. human molecular genetics. 2018 apr 10;27(1):r63-71. View at Publisher View at Google Scholar
liu y, wang x, liu b. a comprehensive review and comparison of existing computational methods for intrinsically disordered protein and region prediction. briefings in bioinformatics. 2017 oct 9;20(1):330-46. View at Publisher View at Google Scholar
pastur-romay la, cedron f, pazos a, porto-pazos ab. deep artificial neural networks and neuromorphic chips for big data analysis: pharmaceutical and bioinformatics applications. international journal of molecular sciences. 2016 aug;17(8):1313. View at Publisher View at Google Scholar
hanson j, yang y, paliwal k, zhou y. improving protein disorder prediction by deep bidirectional long short-term memory recurrent neural networks. bioinformatics. 2016 dec 5;33(5):685-92. View at Publisher View at Google Scholar
to ac. proof copy for josef brinckmann. View at Publisher View at Google Scholar
eswari p. indian versus canadian helpful or ganizations structures and policy: a review based on barr's model of health care governance. j nurs health sci\| volume. 2016 aug;2(3). View at Publisher View at Google Scholar
gummadi p. research & reviews: journal of pharmaceutics and nanotechnology. View at Publisher View at Google Scholar
ç¨»å²¡ç§€æª¢. è›å…‰ä¿¡å·ã‚’åˆ©ç”¨ã—ãŸã‚²ãƒŽãƒ ãƒ»ç”Ÿä½“æƒ…å ±ã®æ¸¬å®šæ‰‹æ³•ã®ç¾çŠ¶ã¨å±•æœ›. é›»æ°—å¦ä¼šè«–æ–‡èªŒ c (é›»åãƒ»æƒ…å ±ãƒ»ã‚·ã‚¹ãƒ†ãƒ éƒ¨é–€èªŒ). 2017 apr 1;137(4):552-60. View at Publisher View at Google Scholar
kabeer ma. research & reviews: journal of dental sciences. View at Publisher View at Google Scholar
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Advanced Techniques in Biology & Medicine
Open Access

Advanced Techniques in Biology & Medicine : Citations & Metrics Report

Important citations (825)

morotomi t, washio a, kitamura c. current and future options for dental pulp therapy. japanese dental science review. 2019 nov 1;55(1):5-11.

badaczewska-dawid a. modelowanie struktury i dynamiki biaÅ‚ek z uÅ¼yciem modeli gruboziarnistych o róÅ¼nej skali rozdzielczoÅ›ci.

rodríguez-guerra pedregal j. development and application of a computational platform for complex molecular design.

hattori lt, benitez cm, gutoski m, aquino nm, lopes hs. a novel approach to protein folding prediction based on long short-term memory networks: a preliminary investigation and analysis. in2018 international joint conference on neural networks (ijcnn) 2018 jul 8 (pp. 1-8). ieee.

jia l, gao h. machine learning in drug discovery and development.

rajesh t. review on heart sound wavelet neural network applications.

khalatbari l, kangavari mr, hosseini s, yin h, cheung nm. mcp: a multi-component learning machine to predict protein secondary structure. computers in biology and medicine. 2019 jul 1;110:144-55.

cárdenas domínguez mi. a computational intelligence analysis of g proteincoupled receptor sequinces for pharmacoproteomic applications.

hanson j, paliwal kk, litfin t, yang y, zhou y. getting to know your neighbor: protein structure prediction comes of age with contextual machine learning. journal of computational biology. 2019 aug 30.

hasic h, buza e, akagic a. a hybrid method for prediction of protein secondary structure based on multiple artificial neural networks. in2017 40th international convention on information and communication technology, electronics and microelectronics (mipro) 2017 may 22 (pp. 1195-1200). ieee.

telenti a, lippert c, chang pc, depristo m. deep learning of genomic variation and regulatory network data. human molecular genetics. 2018 apr 10;27(1):r63-71.

liu y, wang x, liu b. a comprehensive review and comparison of existing computational methods for intrinsically disordered protein and region prediction. briefings in bioinformatics. 2017 oct 9;20(1):330-46.

pastur-romay la, cedron f, pazos a, porto-pazos ab. deep artificial neural networks and neuromorphic chips for big data analysis: pharmaceutical and bioinformatics applications. international journal of molecular sciences. 2016 aug;17(8):1313.

hanson j, yang y, paliwal k, zhou y. improving protein disorder prediction by deep bidirectional long short-term memory recurrent neural networks. bioinformatics. 2016 dec 5;33(5):685-92.

to ac. proof copy for josef brinckmann.

eswari p. indian versus canadian helpful or ganizations structures and policy: a review based on barr's model of health care governance. j nurs health sci| volume. 2016 aug;2(3).

gummadi p. research & reviews: journal of pharmaceutics and nanotechnology.

kabeer ma. research & reviews: journal of dental sciences.

Advanced Techniques in Biology & MedicineOpen Access

Advanced Techniques in Biology & Medicine : Citations & Metrics Report

Important citations (825)

morotomi t, washio a, kitamura c. current and future options for dental pulp therapy. japanese dental science review. 2019 nov 1;55(1):5-11.

badaczewska-dawid a. modelowanie struktury i dynamiki biaÅ‚ek z uÅ¼yciem modeli gruboziarnistych o róÅ¼nej skali rozdzielczoÅ›ci.

rodríguez-guerra pedregal j. development and application of a computational platform for complex molecular design.

hattori lt, benitez cm, gutoski m, aquino nm, lopes hs. a novel approach to protein folding prediction based on long short-term memory networks: a preliminary investigation and analysis. in2018 international joint conference on neural networks (ijcnn) 2018 jul 8 (pp. 1-8). ieee.

jia l, gao h. machine learning in drug discovery and development.

rajesh t. review on heart sound wavelet neural network applications.

khalatbari l, kangavari mr, hosseini s, yin h, cheung nm. mcp: a multi-component learning machine to predict protein secondary structure. computers in biology and medicine. 2019 jul 1;110:144-55.

cárdenas domínguez mi. a computational intelligence analysis of g proteincoupled receptor sequinces for pharmacoproteomic applications.

hanson j, paliwal kk, litfin t, yang y, zhou y. getting to know your neighbor: protein structure prediction comes of age with contextual machine learning. journal of computational biology. 2019 aug 30.

hasic h, buza e, akagic a. a hybrid method for prediction of protein secondary structure based on multiple artificial neural networks. in2017 40th international convention on information and communication technology, electronics and microelectronics (mipro) 2017 may 22 (pp. 1195-1200). ieee.

telenti a, lippert c, chang pc, depristo m. deep learning of genomic variation and regulatory network data. human molecular genetics. 2018 apr 10;27(1):r63-71.

liu y, wang x, liu b. a comprehensive review and comparison of existing computational methods for intrinsically disordered protein and region prediction. briefings in bioinformatics. 2017 oct 9;20(1):330-46.

pastur-romay la, cedron f, pazos a, porto-pazos ab. deep artificial neural networks and neuromorphic chips for big data analysis: pharmaceutical and bioinformatics applications. international journal of molecular sciences. 2016 aug;17(8):1313.

hanson j, yang y, paliwal k, zhou y. improving protein disorder prediction by deep bidirectional long short-term memory recurrent neural networks. bioinformatics. 2016 dec 5;33(5):685-92.

to ac. proof copy for josef brinckmann.

eswari p. indian versus canadian helpful or ganizations structures and policy: a review based on barr's model of health care governance. j nurs health sci| volume. 2016 aug;2(3).

gummadi p. research & reviews: journal of pharmaceutics and nanotechnology.

kabeer ma. research & reviews: journal of dental sciences.

Advanced Techniques in Biology & Medicine
Open Access