Relevant bibliographies by topics / Functional bioinformatics / Journal articles
To see the other types of publications on this topic, follow the link: Functional bioinformatics.

Journal articles on the topic 'Functional bioinformatics'

Author: Grafiati
Published: 4 June 2021
Last updated: 12 February 2022

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Consult the top 50 journal articles for your research on the topic 'Functional bioinformatics.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Browse journal articles on a wide variety of disciplines and organise your bibliography correctly.

1

Edwards, Y. J. K. "Bioinformatics and Functional Genomics." Briefings in Functional Genomics and Proteomics 3, no. 2 (2004): 187–90. http://dx.doi.org/10.1093/bfgp/3.2.187.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Clare, A., A. Karwath, H. Ougham, and R. D. King. "Functional bioinformatics for Arabidopsis thaliana." Bioinformatics 22, no. 9 (2006): 1130–36. http://dx.doi.org/10.1093/bioinformatics/btl051.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Clare, A., A. Karwath, H. Ougham, and R. D. King. "Functional bioinformatics for Arabidopsis thaliana." Bioinformatics 22, no. 13 (2006): 1674. http://dx.doi.org/10.1093/bioinformatics/btl169.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Deng, Youping, Hongwei Wang, Ryuji Hamamoto, David Schaffer, and Shiwei Duan. "Functional Genomics, Genetics, and Bioinformatics." BioMed Research International 2015 (2015): 1–3. http://dx.doi.org/10.1155/2015/184824.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Weichselbaum, David, Bojan Zagrovic, and Anton A. Polyansky. "Fuento: functional enrichment for bioinformatics." Bioinformatics 33, no. 16 (2017): 2604–6. http://dx.doi.org/10.1093/bioinformatics/btx179.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Sorace, James. "Functional bioinformatics the cellular response database." Frontiers in Bioscience 2, no. 1 (1997): a31–36. http://dx.doi.org/10.2741/a160.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Deng, Youping, Hongwei Wang, Ryuji Hamamoto, Shiwei Duan, Mehdi Pirooznia, and Yongsheng Bai. "Functional Genomics, Genetics, and Bioinformatics 2016." BioMed Research International 2016 (2016): 1–3. http://dx.doi.org/10.1155/2016/2625831.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Hatzimaikatis, Vassily. "Bioinformatics and functional genomics: Challenges and opportunities." AIChE Journal 46, no. 12 (2000): 2340–43. http://dx.doi.org/10.1002/aic.690461202.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Khaldi, Nora. "Bioinformatics approaches for identifying new therapeutic bioactive peptides in food." Functional Foods in Health and Disease 2, no. 10 (2012): 325. http://dx.doi.org/10.31989/ffhd.v2i10.80.

Full text
Abstract:
The traditional methods for mining foods for bioactive peptides are tedious and long. Similar to the drug industry, the length of time to identify and deliver a commercial health ingredient that reduces disease symptoms can take anything between 5 to 10 years. Reducing this time and effort is crucial in order to create new commercially viable products with clear and important health benefits. In the past few years, bioinformatics, the science that brings together fast computational biology, and efficient genome mining, is appearing as the long awaited solution to this problem. By quickly mining food genomes for characteristics of certain food therapeutic ingredients, researchers can potentially find new ones in a matter of a few weeks. Yet, surprisingly, very little success has been achieved so far using bioinformatics in mining for food bioactives. The absence of food specific bioinformatic mining tools, the slow integration of both experimental mining and bioinformatics, and the important difference between different experimental platforms are some of the reasons for the slow progress of bioinformatics in the field of functional food and more specifically in bioactive peptide discovery. In this paper I discuss some methods that could be easily translated, using a rational peptide bioinformatics design, to food bioactive peptide mining. I highlight the need for an integrated food peptide database. I also discuss how to better integrate experimental work with bioinformatics in order to improve the mining of food for bioactive peptides, therefore achieving a higher success rates.Keywords: bioactive peptides, bioinformatics, mining food, therapeutic properties, food proteins, functional food.
APA, Harvard, Vancouver, ISO, and other styles
10

Cai, Y. D., and A. J. Doig. "Prediction of Saccharomyces cerevisiae protein functional class from functional domain composition." Bioinformatics 20, no. 8 (2004): 1292–300. http://dx.doi.org/10.1093/bioinformatics/bth085.

Full text
APA, Harvard, Vancouver, ISO, and other styles
11

Parmen, Adibah, MOHD NOOR MAT ISA, FARAH FADWA BENBELGACEM, Hamzah Mohd Salleh, and Ibrahim Ali Noorbatcha. "COMPARATIVE METAGENOMICS ANALYSIS OF PALM OIL MILL EFFLUENT (POME) USING THREE DIFFERENT BIOINFORMATICS PIPELINES." IIUM Engineering Journal 20, no. 1 (2019): 1–11. http://dx.doi.org/10.31436/iiumej.v20i1.909.

Full text
Abstract:
ABSTRACT: The substantial cost reduction and massive production of next-generation sequencing (NGS) data have contributed to the progress in the rapid growth of metagenomics. However, production of the massive amount of data by NGS has revealed the challenges in handling the existing bioinformatics tools related to metagenomics. Therefore, in this research we have investigated an equal set of DNA metagenomics data from palm oil mill effluent (POME) sample using three different freeware bioinformatics pipelines’ websites of metagenomics RAST server (MG-RAST), Integrated Microbial Genomes with Microbiome Samples (IMG/M) and European Bioinformatics Institute (EBI) Metagenomics, in term of the taxonomic assignment and functional analysis. We found that MG-RAST is the quickest among these three pipelines. However, in term of analysis of results, IMG/M provides more variety of phylum with wider percent identities for taxonomical assignment and IMG/M provides the highest carbohydrates, amino acids, lipids, and coenzymes transport and metabolism functional annotation beside the highest in total number of glycoside hydrolase enzymes. Next, in identifying the conserved domain and family involved, EBI Metagenomics would be much more appropriate. All the three bioinformatics pipelines have their own specialties and can be used alternately or at the same time based on the user’s functional preference.
 ABSTRAK: Pengurangan kos dalam skala besar dan pengeluaran data ‘next-generation sequencing’ (NGS) secara besar-besaran telah menyumbang kepada pertumbuhan pesat metagenomik. Walau bagaimanapun, pengeluaran data dalam skala yang besar oleh NGS telah menimbulkan cabaran dalam mengendalikan alat-alat bioinformatika yang sedia ada berkaitan dengan metagenomik. Justeru itu, dalam kajian ini, kami telah menyiasat satu set data metagenomik DNA yang sama dari sampel effluen kilang minyak sawit dengan menggunakan tiga laman web bioinformatik percuma iaitu dari laman web ‘metagenomics RAST server’ (MG-RAST), ‘Integrated Microbial Genomes with Microbiome Samples’ (IMG/M) dan ‘European Bioinformatics Institute’ (EBI) Metagenomics dari segi taksonomi dan analisis fungsi. Kami mendapati bahawa MG-RAST ialah yang paling cepat di antara ketiga-tiga ‘pipeline’, tetapi mengikut keputusan analisa, IMG/M mengeluarkan maklumat philum yang lebih pelbagai bersama peratus identiti yang lebih luas berbanding yang lain untuk pembahagian taksonomi dan IMG/M juga mempunyai bacaan tertinggi dalam hampir semua anotasi fungsional karbohidrat, amino asid, lipid, dan koenzima pengangkutan dan metabolisma malah juga paling tinggi dalam jumlah enzim hidrolase glikosida. Kemudian, untuk mengenal pasti ‘domain’ terpelihara dan keluarga yang terlibat, EBI metagenomics lebih bersesuaian. Ketiga-tiga saluran ‘bioinformatics pipeline’ mempunyai keistimewaan mereka yang tersendiri dan boleh digunakan bersilih ganti dalam masa yang sama berdasarkan pilihan fungsi penggun.
APA, Harvard, Vancouver, ISO, and other styles
12

Torkamani, Ali, and Nicholas J. Schork. "Predicting functional regulatory polymorphisms." Bioinformatics 24, no. 16 (2008): 1787–92. http://dx.doi.org/10.1093/bioinformatics/btn311.

Full text
APA, Harvard, Vancouver, ISO, and other styles
13

Dave, Kirtan, and Atreyi Banerjee. "Bioinformatics Analysis of Functional Relations Between CNPs Regions." Current Bioinformatics 6, no. 1 (2011): 122–28. http://dx.doi.org/10.2174/157489311795222329.

Full text
APA, Harvard, Vancouver, ISO, and other styles
14

Pascual-Montano, Alberto, and Jose M. Carazo. "Efficient functional bioinformatics tools: towards understanding biological processes." EMBnet.journal 16, no. 1 (2010): 31. http://dx.doi.org/10.14806/ej.16.1.184.

Full text
APA, Harvard, Vancouver, ISO, and other styles
15

Smith, Temple F. "Functional genomics—bioinformatics is ready for the challenge." Trends in Genetics 14, no. 7 (1998): 291–93. http://dx.doi.org/10.1016/s0168-9525(98)01508-x.

Full text
APA, Harvard, Vancouver, ISO, and other styles
16

Gromiha, M. M., and Y. Y. Ou. "Bioinformatics approaches for functional annotation of membrane proteins." Briefings in Bioinformatics 15, no. 2 (2013): 155–68. http://dx.doi.org/10.1093/bib/bbt015.

Full text
APA, Harvard, Vancouver, ISO, and other styles
17

Cremona, Marzia A., Hongyan Xu, Kateryna D. Makova, Matthew Reimherr, Francesca Chiaromonte, and Pedro Madrigal. "Functional data analysis for computational biology." Bioinformatics 35, no. 17 (2019): 3211–13. http://dx.doi.org/10.1093/bioinformatics/btz045.

Full text
APA, Harvard, Vancouver, ISO, and other styles
18

Huang, Yu, Haifeng Li, Haiyan Hu, et al. "Systematic discovery of functional modules and context-specific functional annotation of human genome." Bioinformatics 23, no. 13 (2007): i222—i229. http://dx.doi.org/10.1093/bioinformatics/btm222.

Full text
APA, Harvard, Vancouver, ISO, and other styles
19

Pandey, Jayesh, Mehmet Koyutürk, Yohan Kim, Wojciech Szpankowski, Shankar Subramaniam, and Ananth Grama. "Functional annotation of regulatory pathways." Bioinformatics 23, no. 13 (2007): i377—i386. http://dx.doi.org/10.1093/bioinformatics/btm203.

Full text
APA, Harvard, Vancouver, ISO, and other styles
20

Malod-Dognin, Noël, and Nataša Pržulj. "Functional geometry of protein interactomes." Bioinformatics 35, no. 19 (2019): 3727–34. http://dx.doi.org/10.1093/bioinformatics/btz146.

Full text
Abstract:
Abstract Motivation Protein–protein interactions (PPIs) are usually modeled as networks. These networks have extensively been studied using graphlets, small induced subgraphs capturing the local wiring patterns around nodes in networks. They revealed that proteins involved in similar functions tend to be similarly wired. However, such simple models can only represent pairwise relationships and cannot fully capture the higher-order organization of protein interactomes, including protein complexes. Results To model the multi-scale organization of these complex biological systems, we utilize simplicial complexes from computational geometry. The question is how to mine these new representations of protein interactomes to reveal additional biological information. To address this, we define simplets, a generalization of graphlets to simplicial complexes. By using simplets, we define a sensitive measure of similarity between simplicial complex representations that allows for clustering them according to their data types better than clustering them by using other state-of-the-art measures, e.g. spectral distance, or facet distribution distance. We model human and baker’s yeast protein interactomes as simplicial complexes that capture PPIs and protein complexes as simplices. On these models, we show that our newly introduced simplet-based methods cluster proteins by function better than the clustering methods that use the standard PPI networks, uncovering the new underlying functional organization of the cell. We demonstrate the existence of the functional geometry in the protein interactome data and the superiority of our simplet-based methods to effectively mine for new biological information hidden in the complexity of the higher-order organization of protein interactomes. Availability and implementation Codes and datasets are freely available at http://www0.cs.ucl.ac.uk/staff/natasa/Simplets/. Supplementary information Supplementary data are available at Bioinformatics online.
APA, Harvard, Vancouver, ISO, and other styles
21

Wang, Dong, Juan Wang, Ming Lu, Fei Song, and Qinghua Cui. "Inferring the human microRNA functional similarity and functional network based on microRNA-associated diseases." Bioinformatics 26, no. 13 (2010): 1644–50. http://dx.doi.org/10.1093/bioinformatics/btq241.

Full text
APA, Harvard, Vancouver, ISO, and other styles
22

Standley, Daron M., Hiroyuki Toh, and Haruki Nakamura. "S08I2 Functional Annotation Sequence-weighted Structure Alignments(Bioinformatics in the Era of Structural Proteomics)." Seibutsu Butsuri 47, supplement (2007): S11. http://dx.doi.org/10.2142/biophys.47.s11_3.

Full text
APA, Harvard, Vancouver, ISO, and other styles
23

WONG, LIMSOON. "Kleisli, a functional query system." Journal of Functional Programming 10, no. 1 (2000): 19–56. http://dx.doi.org/10.1017/s0956796899003585.

Full text
Abstract:
Kleisli is a modern data integration system that has made a significant impact on bioinformatics data integration. This paper contains a brief introduction to the Kleisli system and an example to illustrate its uses in the bioinformatics arena. The primary query language provided by Kleisli is called CPL, which is a functional query language whose surface syntax is based on the comprehension syntax. Kleisli is itself implemented using the functional language SML. So this paper also describes the influence of functional programming research that benefits the Kleisli system, especially the less obvious ones at the implementation level.Availability. Kleisli has been commercialized under the name “KRIS”. It is available from Kris Technology Inc., 713 Santa Cruz Ave, #2, Menlo Park, CA 94025, USA. Direct email to info@kris-inc.com and web browser to http://www.kris-inc.com.
APA, Harvard, Vancouver, ISO, and other styles
24

Sansom, Clare. "CCP11 Group Meeting—Towards the Functional Analysis of Microarrays." Comparative and Functional Genomics 3, no. 5 (2002): 451–54. http://dx.doi.org/10.1002/cfg.201.

Full text
Abstract:
The CCP11 project [2] aims to foster bioinformatics in the UK through conferences, workshops and the provision of Web resources. In March 2002, CCP11 held a meeting in Manchester, UK, on the functional analysis of microarrays. This was part of Manchester BioinformaticsWeek—three consecutive short bioinformatics meetings held in the attractive setting of the Chancellor's Conference Centre at the University of Manchester. The other meetings in the series were a workshop on ontologies and the 12th Annual MASAMB (Mathematical and Statistical Aspects of Molecular Biology) Conference. Many delegates were able to attend more than one meeting, which led to a useful cross-fertilization of ideas across the bioinformatics community. The CCP11 meeting shared with MASAMB a strong emphasis on the statistical analysis and interpretation of data—most often image intensity data.
APA, Harvard, Vancouver, ISO, and other styles
25

Urbanczik, R., and C. Wagner. "Functional stoichiometric analysis of metabolic networks." Bioinformatics 21, no. 22 (2005): 4176–80. http://dx.doi.org/10.1093/bioinformatics/bti674.

Full text
APA, Harvard, Vancouver, ISO, and other styles
26

Pazos, F., A. Rausell, and A. Valencia. "Phylogeny-independent detection of functional residues." Bioinformatics 22, no. 12 (2006): 1440–48. http://dx.doi.org/10.1093/bioinformatics/btl104.

Full text
APA, Harvard, Vancouver, ISO, and other styles
27

Pandey, J., M. Koyuturk, S. Subramaniam, and A. Grama. "Functional coherence in domain interaction networks." Bioinformatics 24, no. 16 (2008): i28—i34. http://dx.doi.org/10.1093/bioinformatics/btn296.

Full text
APA, Harvard, Vancouver, ISO, and other styles
28

Weisman, David, Michie Yasuda, and Jennifer L. Bowen. "FunFrame: functional gene ecological analysis pipeline." Bioinformatics 29, no. 9 (2013): 1212–14. http://dx.doi.org/10.1093/bioinformatics/btt123.

Full text
APA, Harvard, Vancouver, ISO, and other styles
29

Croset, Samuel, John P. Overington, and Dietrich Rebholz-Schuhmann. "The functional therapeutic chemical classification system." Bioinformatics 30, no. 6 (2013): 876–83. http://dx.doi.org/10.1093/bioinformatics/btt628.

Full text
APA, Harvard, Vancouver, ISO, and other styles
30

Ma, C. X., R. Wu, and G. Casella. "FunMap: functional mapping of complex traits." Bioinformatics 20, no. 11 (2004): 1808–11. http://dx.doi.org/10.1093/bioinformatics/bth156.

Full text
APA, Harvard, Vancouver, ISO, and other styles
31

Donald, J. E., and E. I. Shakhnovich. "Determining functional specificity from protein sequences." Bioinformatics 21, no. 11 (2005): 2629–35. http://dx.doi.org/10.1093/bioinformatics/bti396.

Full text
APA, Harvard, Vancouver, ISO, and other styles
32

Frishman, D., K. Albermann, J. Hani, et al. "Functional and structural genomics using PEDANT." Bioinformatics 17, no. 1 (2001): 44–57. http://dx.doi.org/10.1093/bioinformatics/17.1.44.

Full text
APA, Harvard, Vancouver, ISO, and other styles
33

Bleazard, Thomas, Janine A. Lamb, and Sam Griffiths-Jones. "Bias in microRNA functional enrichment analysis." Bioinformatics 31, no. 10 (2015): 1592–98. http://dx.doi.org/10.1093/bioinformatics/btv023.

Full text
APA, Harvard, Vancouver, ISO, and other styles
34

Rao, Allam Appa, Hanuman Thota, Ramachandra Sridhar Gumpeny, et al. "Bioinformatics analysis of diabetic retinopathy using functional protein sequences." Medical Hypotheses 70, no. 1 (2008): 148–55. http://dx.doi.org/10.1016/j.mehy.2007.03.033.

Full text
APA, Harvard, Vancouver, ISO, and other styles
35

Sinchaikul, Supachok, Boonyaras Sookkheo, Supachai Topanuruk, Hsueh-Fen Juan, Suree Phutrakul, and Shui-Tein Chen. "Bioinformatics, functional genomics, and proteomics study of Bacillus sp." Journal of Chromatography B 771, no. 1-2 (2002): 261–87. http://dx.doi.org/10.1016/s1570-0232(02)00054-5.

Full text
APA, Harvard, Vancouver, ISO, and other styles
36

Ecale Zhou, Carol L., Stephanie Malfatti, Jeffrey Kimbrel, et al. "multiPhATE: bioinformatics pipeline for functional annotation of phage isolates." Bioinformatics 35, no. 21 (2019): 4402–4. http://dx.doi.org/10.1093/bioinformatics/btz258.

Full text
Abstract:
Abstract Summary To address the need for improved phage annotation tools that scale, we created an automated throughput annotation pipeline: multiple-genome Phage Annotation Toolkit and Evaluator (multiPhATE). multiPhATE is a throughput pipeline driver that invokes an annotation pipeline (PhATE) across a user-specified set of phage genomes. This tool incorporates a de novo phage gene calling algorithm and assigns putative functions to gene calls using protein-, virus- and phage-centric databases. multiPhATE’s modular construction allows the user to implement all or any portion of the analyses by acquiring local instances of the desired databases and specifying the desired analyses in a configuration file. We demonstrate multiPhATE by annotating two newly sequenced Yersinia pestis phage genomes. Within multiPhATE, the PhATE processing pipeline can be readily implemented across multiple processors, making it adaptable for throughput sequencing projects. Software documentation assists the user in configuring the system. Availability and implementation multiPhATE was implemented in Python 3.7, and runs as a command-line code under Linux or Unix. multiPhATE is freely available under an open-source BSD3 license from https://github.com/carolzhou/multiPhATE. Instructions for acquiring the databases and third-party codes used by multiPhATE are included in the distribution README file. Users may report bugs by submitting to the github issues page associated with the multiPhATE distribution. Supplementary information Supplementary data are available at Bioinformatics online.
APA, Harvard, Vancouver, ISO, and other styles
37

Cline, M. S., and R. Karchin. "Using bioinformatics to predict the functional impact of SNVs." Bioinformatics 27, no. 4 (2010): 441–48. http://dx.doi.org/10.1093/bioinformatics/btq695.

Full text
APA, Harvard, Vancouver, ISO, and other styles
38

Ilyin, Sergey E., Alejandro Bernal, Daniel Horowitz, Claudia K. Derian, and Hong Xin. "Functional informatics: convergence and integration of automation and bioinformatics." Pharmacogenomics 5, no. 6 (2004): 721–30. http://dx.doi.org/10.1517/14622416.5.6.721.

Full text
APA, Harvard, Vancouver, ISO, and other styles
39

Moreau, Y., F. De Smet, G. Thijs, K. Marchal, and B. De Moor. "Functional bioinformatics of microarray data: from expression to regulation." Proceedings of the IEEE 90, no. 11 (2002): 1722–43. http://dx.doi.org/10.1109/jproc.2002.804681.

Full text
APA, Harvard, Vancouver, ISO, and other styles
40

Takenaka, M., and E. Imai. "Functional genomics in nephrology: construction and application of bioinformatics." Clinical and Experimental Nephrology 4, no. 4 (2000): 281–85. http://dx.doi.org/10.1007/s101570070002.

Full text
APA, Harvard, Vancouver, ISO, and other styles
41

Wass, Mark N., and Michael J. E. Sternberg. "ConFunc—functional annotation in the twilight zone." Bioinformatics 24, no. 6 (2008): 798–806. http://dx.doi.org/10.1093/bioinformatics/btn037.

Full text
APA, Harvard, Vancouver, ISO, and other styles
42

McDermott, J., R. Bumgarner, and R. Samudrala. "Functional annotation from predicted protein interaction networks." Bioinformatics 21, no. 15 (2005): 3217–26. http://dx.doi.org/10.1093/bioinformatics/bti514.

Full text
APA, Harvard, Vancouver, ISO, and other styles
43

Kim, Y., M. Koyuturk, U. Topkara, A. Grama, and S. Subramaniam. "Inferring functional information from domain co-evolution." Bioinformatics 22, no. 1 (2005): 40–49. http://dx.doi.org/10.1093/bioinformatics/bti723.

Full text
APA, Harvard, Vancouver, ISO, and other styles
44

Yosef, N., A. Kaufman, and E. Ruppin. "Inferring Functional Pathways from Multi-Perturbation Data." Bioinformatics 22, no. 14 (2006): e539-e546. http://dx.doi.org/10.1093/bioinformatics/btl204.

Full text
APA, Harvard, Vancouver, ISO, and other styles
45

Huttenhower, C., and O. G. Troyanskaya. "Assessing the functional structure of genomic data." Bioinformatics 24, no. 13 (2008): i330—i338. http://dx.doi.org/10.1093/bioinformatics/btn160.

Full text
APA, Harvard, Vancouver, ISO, and other styles
46

Huttenhower, C., M. Schroeder, M. D. Chikina, and O. G. Troyanskaya. "The Sleipnir library for computational functional genomics." Bioinformatics 24, no. 13 (2008): 1559–61. http://dx.doi.org/10.1093/bioinformatics/btn237.

Full text
APA, Harvard, Vancouver, ISO, and other styles
47

Berriz, G. F., J. E. Beaver, C. Cenik, M. Tasan, and F. P. Roth. "Next generation software for functional trend analysis." Bioinformatics 25, no. 22 (2009): 3043–44. http://dx.doi.org/10.1093/bioinformatics/btp498.

Full text
APA, Harvard, Vancouver, ISO, and other styles
48

Gogleva, Anna, Hajk-Georg Drost, and Sebastian Schornack. "SecretSanta: flexible pipelines for functional secretome prediction." Bioinformatics 34, no. 13 (2018): 2295–96. http://dx.doi.org/10.1093/bioinformatics/bty088.

Full text
APA, Harvard, Vancouver, ISO, and other styles
49

van den Boom, Willem, Callie Mao, Rebecca A. Schroeder, and David B. Dunson. "Extrema-weighted feature extraction for functional data." Bioinformatics 34, no. 14 (2018): 2457–64. http://dx.doi.org/10.1093/bioinformatics/bty120.

Full text
APA, Harvard, Vancouver, ISO, and other styles
50

Rivas-Astroza, M., D. Xie, X. Cao, and S. Zhong. "Mapping personal functional data to personal genomes." Bioinformatics 27, no. 24 (2011): 3427–29. http://dx.doi.org/10.1093/bioinformatics/btr578.

Full text
APA, Harvard, Vancouver, ISO, and other styles
You might also be interested in the bibliographies on the topic 'Functional bioinformatics' for other source types:
Dissertations / Theses Books
We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!

To the bibliography