Protein classification of beach pea (Lathyrus maritimus L.)

2001 ◽  
Vol 75 (2) ◽  
pp. 145-153 ◽  
Author(s):  
U.D. Chavan ◽  
D.B. McKenzie ◽  
F. Shahidi
Keyword(s):  
Protein Classification ◽  
Lathyrus Maritimus ◽  
Beach Pea

The pattern of seed development and maturation in beach pea (Lathyrus maritimus)

2003 ◽  
Vol 81 (6) ◽  
pp. 531-540 ◽  
Author(s):  
Gurusamy Chinnasamy ◽  
Arya Kumar Bal
Keyword(s):  
Seed Development ◽  
Seed Coat ◽  
Dry Weight ◽  
Growth Stages ◽  
Protein Accumulation ◽  
Grass Pea ◽  
Hard Seed ◽  
Pea Seeds ◽  
Lathyrus Maritimus ◽  
Beach Pea

The developmental patterns of seed, seed coat, and hardseededness were studied in naturally growing crop plants of beach pea (Lathyrus maritimus (L.) Bigel.) at six reproductive growth stages (S1–S6). Grass pea (Lathyrus sativus L.) seeds were used for comparison in some experiments. The accumulation of fresh and dry weight in pod shell and seed of beach pea and pod shell of grass pea followed an almost sigmoidal pattern. However, grass pea seed showed a linear pattern of weight accumulation. During maturation, moisture content of pod shells and seeds decreased because of dehydration. Beach pea seeds were able to germinate precociously at S4. Seeds collected between S1 and S3 failed to germinate because of immaturity, whereas the development of hard seed coats prevented germination in seeds gathered at S5 and S6. An imbibition test revealed that hardseededness completely prevented water absorption of S5 and S6 seeds even after 24 days of soaking. In grass pea, precocious seed germination was observed at S3. However, speed of germination, germination percentage, seedling length and dry weight increased as seeds approached maturity. Lipid and protein accumulation in seeds of both species increased progressively with maturity and showed a positive correlation with seed weight accumulation. In both beach pea and grass pea seeds, S6 was identified as a physiological maturity stage.Key words: beach pea, grass pea, hard seed, imbibition, Lathyrus, seed coat, seed development, water impermeability.

scholarly journals Functional classification of transcription factor binding sites: Information content as a metric

2006 ◽  
Vol 3 (1) ◽  
pp. 32-44 ◽  
Author(s):  
D. Ashok Reddy ◽  
B. V. L. S. Prasad ◽  
Chanchal K. Mitra
Keyword(s):  
Transcription Factor ◽  
Information Content ◽  
Binding Sites ◽  
Transcription Factor Binding Sites ◽  
Transcription Factor Binding ◽  
Protein Classification ◽  
Specific Gene ◽  
Functional Classification ◽  
Factor Binding

Summary The information content (relative entropy) of transcription factor binding sites (TFBS) is used to classify the transcription factors (TFs). The TF classes are clustered based on the TFBS clustering using information content. Any TF belonging to the TF class cluster has a chance of binding to any TFBS of the clustered group. Thus, out of the 41 TFBS (in humans), perhaps only 5 -10 TFs may be actually needed and in case of mouse instead of 13 TFs, we may have actually 5 or so TFs. The JASPAR database of TFBS are used in this study. The experimental data on TFs of specific gene expression from TRRD database is also coinciding with our computational results. This gives us a new way to look at the protein classification- not based on their structure or function but by the nature of their TFBS.

scholarly journals Rat Protein’s Enzyme Class Classification Using Machine Learning

2019 ◽  
Vol 8 (6) ◽  
pp. 655-663
Keyword(s):  
Machine Learning ◽  
Statistical Technique ◽  
Research Area ◽  
Experimental Result ◽  
Protein Classification ◽  
Computational Technique ◽  
Unknown Protein ◽  
Enzyme Class ◽  
Protein Enzyme

In the current era, bioinformatics has been an emerging research area in the context of protein enzyme classification from the unknown protein data. In bioinformatics, the prime goal is to manipulate the protein data and develop a computational technique to classify and predict the appropriate features for function predictions. In this context, several machine learning and statistical technique have been designed for classification of data. The classification of protein data is one the challenging task and generally the classification of protein data has been done on human protein data. In this article, we have considered rat enzyme class for classification and predictions. Here we have used like CRT, CHAID, C5.0, NEURAL, SVM, and Bayesian for classification of protein data and to measure the performance of the model, the accuracy, specificity, sensitivity, precision, recall, f-measures and MCC have been used. The experimental result highlights that the some of the protein data are imbalance that affects the performance. In this experiment, the Lyases, Isomerases and Ligases class of data are imbalanced and affect the performance of the models. The experimental results highlight that the C5.0 gives 91.5% accuracy and takes only 4 second for computation and can be used for protein classification and prediction of protein data.

scholarly journals Variable Selection from a Feature Representing Protein Sequences: A Case of Classification on Bacterial Type IV Secreted Effectors

2020 ◽  
Author(s):  
Jian Zhang ◽  
Lixin Lv ◽  
Donglei Lu ◽  
Denan Kong ◽  
Mohammed Abdoh Ali Al-Alashaari ◽  
...  
Keyword(s):  
Variable Selection ◽  
Protein Sequences ◽  
Biological Research ◽  
Protein Classification ◽  
Ensemble Classifiers ◽  
Type Iv ◽  
Protein Prediction ◽  
Kernel Set ◽  
Bacterial Type

Abstract Background: Classification of certain proteins with specific functions is momentous for biological research. Encoding approaches of protein sequences for feature extraction play an important role in protein classification. Many computational methods (namely classifiers) are used for classification on protein sequences according to various encoding approaches. Commonly, protein sequences keep certain labels corresponding to different categories of biological functions (e.g., bacterial type IV secreted effectors or not), which makes protein prediction a fantasy. As to protein prediction, a kernel set of protein sequences keeping certain labels certified by biological experiments should be existent in advance. However, it has been hardly ever seen in prevailing researches. Therefore, unsupervised learning rather than supervised learning (e.g. classification) should be considered. As to protein classification, various classifiers may help to evaluate the effectiveness of different encoding approaches. Besides, variable selection from an encoded feature representing protein sequences is an important issue that also needs to be considered.Results: Focusing on the latter problem, we propose a new method for variable selection from an encoded feature representing protein sequences. Taking a benchmark dataset as a case, experiments are made to identify bacterial type IV secreted effectors from protein sequences, which indicates the effectiveness of our method. Conclusions: Certain variables other than an encoded feature they belong to do work for discrimination between different types of proteins. In addition, ensemble classifiers with an automatic assignment of different base classifiers do achieve a better classification result.

Fatty acid and elemental composition of mature seeds of beach pea [Lathyrus maritimus (L.) Bigel.]

2004 ◽  
Vol 84 (1) ◽  
pp. 65-69
Author(s):  
Gurusamy Chinnasamy, Arya Kumar Bal ◽  
David Bruce McKenzie
Keyword(s):  
Fatty Acids ◽  
Fatty Acid ◽  
Free Fatty Acids ◽  
Elemental Composition ◽  
Seed Coat ◽  
Relative Weight ◽  
Pea Seeds ◽  
Lathyrus Maritimus ◽  
Beach Pea ◽  
Seed Coats

This study was conducted to determine the fatty acid composition of phospholipids (PL), monoglycerides (MG), diglycerides (DG), free fatty acids (FFA) and triglycerides (TG) of mature beach pea seeds and the elemental composition of mature beach pea seed coats and embryos. In beach pea seeds, PL were dominated by C18:2 and C16:0 and MG contained high quantities of C18:2, C16:0 and C18:1. Diglycerides showed high C18:0, C16:0 and C18:2. Free fatty acids were dominated by C18:2, C16:0, C18:1 and C18:0, and TG were dominated by C18:1, C18:0 and C16:0. Energy dispersive X-ray microanalysis revealed K as the most abundant element in whole seed, seed coat and embryo. However, embryos showed significantly higher relative weight percentage of K than whole seeds and seed coats. Whole seeds and embryos contained higher P, S and Cl relative weight percentages than seed coats. Seed coats contained higher Ca, Na a nd Mg relative weight percentages than embryos. Aluminium, Si, Mn, Fe, Cu and Zn distribution between seed coat and embryo was uniform. Key words: Beach pea, element, fatty acid, Lathyrus maritimus L., lipid, seed

Chemical composition of beach pea (Lathyrus maritimus L.) plant parts

1999 ◽  
Vol 64 (1) ◽  
pp. 39-44 ◽  
Author(s):  
F Shahidi ◽  
U.D Chavan ◽  
A.K Bal ◽  
D.B McKenzie
Keyword(s):  
Chemical Composition ◽  
Plant Parts ◽  
Lathyrus Maritimus ◽  
Beach Pea

ANTIOXIDANT ACTIVITY OF PHENOLIC FRACTIONS OF BEACH PEA (LATHYRUS MARITIMUS L.)

1999 ◽  
Vol 6 (1) ◽  
pp. 1-11 ◽  
Author(s):  
UTTAM D. CHAVAN ◽  
RYSZARD AMAROWICZ ◽  
FEREIDOON SHAHIDI
Keyword(s):  
Antioxidant Activity ◽  
Lathyrus Maritimus ◽  
Beach Pea

Nodulation of beach pea (Lathyrus maritimus [L.] Bigel.) induced by different strains of rhizobia

1999 ◽  
Vol 79 (2) ◽  
pp. 239-242 ◽  
Author(s):  
C. Gurusamy ◽  
A. K. Bal ◽  
D. B. McKenzie
Keyword(s):  
Root Nodules ◽  
Cold Climate ◽  
Rhizobial Strain ◽  
Grass Pea ◽  
Native Strain ◽  
Legume Crop ◽  
Lathyrus Maritimus ◽  
Different Strains ◽  
Lathyrus Sativus L ◽  
Beach Pea

In an attempt to screen the most effective rhizobial strain for the potential cold-climate legume crop beach pea (Lathyrus maritimus L.), rhizobia from eight different species of Lathyrus were tested along with the native strain on a 9-wk-long pot culture. The native strain, ACCCRC, isolated from beach pea proved to be the most effective. The tropical legume grass pea (L. sativus L.) tested with the above strains failed to nodulate with ACCCRC, USDA 2422 and USDA 2446. Oleosome content of nodules assessed from histological sections reveals higher numbers in beach pea than in grass pea. Key words: Lathyrus maritimus L., Lathyrus sativus L., root nodules, oleosomes (lipid bodies)

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